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  1. README.md +97 -195
  2. generation_config.json +253 -0
  3. training_args.bin +1 -1
README.md CHANGED
@@ -1,199 +1,101 @@
1
  ---
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  library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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-
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- <!-- Provide a quick summary of what the model is/does. -->
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-
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-
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-
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- ## Model Details
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-
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- ### Model Description
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-
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- <!-- Provide a longer summary of what this model is. -->
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-
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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-
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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-
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- ### Model Sources [optional]
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-
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- <!-- Provide the basic links for the model. -->
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-
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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-
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- ## Uses
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-
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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-
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- ### Direct Use
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-
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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-
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- [More Information Needed]
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-
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- ### Downstream Use [optional]
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-
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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-
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- [More Information Needed]
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-
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- ### Out-of-Scope Use
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-
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-
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- [More Information Needed]
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-
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- ## Bias, Risks, and Limitations
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-
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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-
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- [More Information Needed]
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-
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- ### Recommendations
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-
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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-
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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-
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- ## How to Get Started with the Model
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-
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- Use the code below to get started with the model.
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-
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- [More Information Needed]
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-
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- ## Training Details
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-
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- ### Training Data
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-
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- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-
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- [More Information Needed]
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-
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- ### Training Procedure
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-
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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-
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- #### Preprocessing [optional]
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-
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- [More Information Needed]
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-
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-
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- #### Training Hyperparameters
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-
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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-
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- #### Speeds, Sizes, Times [optional]
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-
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-
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- [More Information Needed]
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-
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- ## Evaluation
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-
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- <!-- This section describes the evaluation protocols and provides the results. -->
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-
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- ### Testing Data, Factors & Metrics
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-
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- #### Testing Data
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-
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- <!-- This should link to a Dataset Card if possible. -->
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-
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- [More Information Needed]
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-
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- #### Factors
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-
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-
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- [More Information Needed]
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-
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- #### Metrics
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-
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-
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- [More Information Needed]
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-
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- ### Results
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-
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- [More Information Needed]
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-
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- #### Summary
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-
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-
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-
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- ## Model Examination [optional]
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-
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- <!-- Relevant interpretability work for the model goes here -->
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-
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- [More Information Needed]
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-
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- ## Environmental Impact
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-
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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-
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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-
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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-
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- ## Technical Specifications [optional]
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-
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- ### Model Architecture and Objective
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-
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- [More Information Needed]
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-
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- ### Compute Infrastructure
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- [More Information Needed]
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-
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- #### Hardware
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- [More Information Needed]
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- #### Software
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- [More Information Needed]
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- ## Citation [optional]
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-
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
1
  ---
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  library_name: transformers
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: whisper-small-CV-Fleurs-lg-313hrs-v1
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+ results: []
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # whisper-small-CV-Fleurs-lg-313hrs-v1
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Cer: 0.0803
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+ - Loss: 0.7644
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+ - Wer: 0.2848
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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+ - optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 30
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
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+ |:-------------:|:-----:|:-------:|:------:|:---------------:|:------:|
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+ | 0.9959 | 1.0 | 30487 | 0.4780 | 0.5805 | 1.0507 |
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+ | 0.2917 | 2.0 | 60974 | 0.8109 | 0.4413 | 1.4684 |
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+ | 0.1945 | 3.0 | 91461 | 0.1449 | 0.4016 | 0.4604 |
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+ | 0.139 | 4.0 | 121948 | 0.0933 | 0.3980 | 0.3740 |
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+ | 0.0986 | 5.0 | 152435 | 0.0910 | 0.4101 | 0.3542 |
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+ | 0.0698 | 6.0 | 182922 | 0.0935 | 0.4245 | 0.3447 |
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+ | 0.0515 | 7.0 | 213409 | 0.0824 | 0.4571 | 0.3246 |
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+ | 0.0412 | 8.0 | 243896 | 0.0843 | 0.4769 | 0.3185 |
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+ | 0.0362 | 9.0 | 274383 | 0.0812 | 0.4909 | 0.3106 |
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+ | 0.0339 | 10.0 | 304870 | 0.0819 | 0.5001 | 0.3119 |
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+ | 0.0301 | 11.0 | 335357 | 0.0848 | 0.5248 | 0.3142 |
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+ | 0.0243 | 12.0 | 365844 | 0.0843 | 0.5246 | 0.3045 |
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+ | 0.0199 | 13.0 | 396331 | 0.0801 | 0.5518 | 0.3004 |
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+ | 0.0167 | 14.0 | 426818 | 0.0857 | 0.5877 | 0.3085 |
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+ | 0.0143 | 15.0 | 457305 | 0.0806 | 0.5835 | 0.3024 |
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+ | 0.0124 | 16.0 | 487792 | 0.0819 | 0.5982 | 0.2995 |
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+ | 0.011 | 17.0 | 518279 | 0.0845 | 0.5933 | 0.3022 |
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+ | 0.0099 | 18.0 | 548766 | 0.0866 | 0.6195 | 0.2996 |
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+ | 0.0088 | 19.0 | 579253 | 0.0825 | 0.6577 | 0.2966 |
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+ | 0.0079 | 20.0 | 609740 | 0.0843 | 0.6416 | 0.2991 |
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+ | 0.0073 | 21.0 | 640227 | 0.0810 | 0.6536 | 0.2938 |
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+ | 0.0065 | 22.0 | 670714 | 0.0829 | 0.6708 | 0.2990 |
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+ | 0.006 | 23.0 | 701201 | 0.0867 | 0.6726 | 0.2978 |
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+ | 0.0056 | 24.0 | 731688 | 0.0819 | 0.6944 | 0.2921 |
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+ | 0.0053 | 25.0 | 762175 | 0.0824 | 0.6845 | 0.2942 |
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+ | 0.0049 | 26.0 | 792662 | 0.0840 | 0.6856 | 0.2926 |
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+ | 0.0046 | 27.0 | 823149 | 0.0829 | 0.6926 | 0.2914 |
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+ | 0.0042 | 28.0 | 853636 | 0.0832 | 0.7022 | 0.2866 |
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+ | 0.004 | 29.0 | 884123 | 0.0800 | 0.7230 | 0.2898 |
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+ | 0.0037 | 30.0 | 914610 | 0.0824 | 0.7287 | 0.2925 |
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+ | 0.0034 | 31.0 | 945097 | 0.0801 | 0.7363 | 0.2860 |
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+ | 0.0033 | 32.0 | 975584 | 0.0803 | 0.7497 | 0.2866 |
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+ | 0.0032 | 33.0 | 1006071 | 0.0814 | 0.7478 | 0.2827 |
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+ | 0.0029 | 34.0 | 1036558 | 0.0791 | 0.7292 | 0.2845 |
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+ | 0.0028 | 35.0 | 1067045 | 0.0829 | 0.7657 | 0.2891 |
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+ | 0.0026 | 36.0 | 1097532 | 0.0803 | 0.7644 | 0.2848 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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