File size: 2,089 Bytes
7f83d46 7a7a643 7f83d46 7a7a643 7f83d46 7a7a643 7f83d46 7a7a643 7f83d46 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
library_name: transformers
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- kneth90/test_data_set_2
metrics:
- wer
model-index:
- name: Whisper Small ID - Kenn
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Test Dataset 2
type: kneth90/test_data_set_2
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 63.92405063291139
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small ID - Kenn
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Test Dataset 2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6740
- Wer: 63.9241
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.0008 | 41.6667 | 1000 | 1.5316 | 64.9789 |
| 0.0001 | 83.3333 | 2000 | 1.6316 | 64.3460 |
| 0.0 | 125.0 | 3000 | 1.6618 | 64.5570 |
| 0.0 | 166.6667 | 4000 | 1.6740 | 63.9241 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|