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Vishnou/distilbert_base_SST2

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  1. README.md +21 -21
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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  license: apache-2.0
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- base_model: distilbert-base-uncased-finetuned-sst-2-english
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9151376146788991
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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
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilbert_base_SST2
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- This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the sst2 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3690
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- - Accuracy: 0.9151
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  ## Model description
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@@ -64,22 +64,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.1335 | 0.06 | 500 | 0.5579 | 0.8911 |
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- | 0.1666 | 0.12 | 1000 | 0.5413 | 0.8876 |
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- | 0.1778 | 0.18 | 1500 | 0.7077 | 0.8544 |
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- | 0.1746 | 0.24 | 2000 | 0.5727 | 0.875 |
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- | 0.1632 | 0.3 | 2500 | 0.4972 | 0.8979 |
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- | 0.1675 | 0.36 | 3000 | 0.4742 | 0.8991 |
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- | 0.1573 | 0.42 | 3500 | 0.4943 | 0.8956 |
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- | 0.1525 | 0.48 | 4000 | 0.4907 | 0.8819 |
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- | 0.1394 | 0.53 | 4500 | 0.5010 | 0.8899 |
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- | 0.1458 | 0.59 | 5000 | 0.5461 | 0.8876 |
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- | 0.1588 | 0.65 | 5500 | 0.3364 | 0.9094 |
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- | 0.1373 | 0.71 | 6000 | 0.4198 | 0.9163 |
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- | 0.138 | 0.77 | 6500 | 0.3466 | 0.9128 |
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- | 0.1383 | 0.83 | 7000 | 0.4064 | 0.9094 |
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- | 0.1371 | 0.89 | 7500 | 0.4083 | 0.9002 |
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- | 0.1373 | 0.95 | 8000 | 0.3690 | 0.9151 |
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: distilbert-base-uncased
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8967889908256881
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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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  # distilbert_base_SST2
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the sst2 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3718
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+ - Accuracy: 0.8968
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4401 | 0.06 | 500 | 0.3732 | 0.8417 |
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+ | 0.3465 | 0.12 | 1000 | 0.3451 | 0.8761 |
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+ | 0.3408 | 0.18 | 1500 | 0.3465 | 0.8612 |
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+ | 0.3059 | 0.24 | 2000 | 0.4580 | 0.8589 |
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+ | 0.2974 | 0.3 | 2500 | 0.3338 | 0.8830 |
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+ | 0.3023 | 0.36 | 3000 | 0.4487 | 0.8475 |
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+ | 0.2636 | 0.42 | 3500 | 0.4330 | 0.8888 |
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+ | 0.2558 | 0.48 | 4000 | 0.4193 | 0.8876 |
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+ | 0.2466 | 0.53 | 4500 | 0.4343 | 0.8945 |
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+ | 0.2393 | 0.59 | 5000 | 0.4935 | 0.875 |
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+ | 0.2279 | 0.65 | 5500 | 0.3818 | 0.8876 |
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+ | 0.2181 | 0.71 | 6000 | 0.4003 | 0.8968 |
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+ | 0.2245 | 0.77 | 6500 | 0.3496 | 0.9048 |
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+ | 0.2279 | 0.83 | 7000 | 0.3759 | 0.9014 |
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+ | 0.2152 | 0.89 | 7500 | 0.4037 | 0.8899 |
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+ | 0.2174 | 0.95 | 8000 | 0.3718 | 0.8968 |
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  ### Framework versions
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