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derek-harnett
/
movie-review-classifier

Text Classification
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distilbert
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  1. README.md +9 -7
  2. model.safetensors +1 -1
  3. runs/Jun07_15-43-15_13ebd0311d0e/events.out.tfevents.1717775159.13ebd0311d0e.2192.0 +3 -0
  4. runs/Jun07_15-43-15_13ebd0311d0e/events.out.tfevents.1717776628.13ebd0311d0e.2192.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2841
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- - Accuracy: 0.8828
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- - Precision: 0.8690
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- - Recall: 0.9017
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- - F1: 0.8851
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  ## Model description
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@@ -49,13 +49,15 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 1.0 | 157 | 0.2841 | 0.8828 | 0.8690 | 0.9017 | 0.8851 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3105
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+ - Accuracy: 0.9207
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+ - Precision: 0.9131
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+ - Recall: 0.9296
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+ - F1: 0.9213
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.3135 | 1.0 | 782 | 0.2359 | 0.9134 | 0.8826 | 0.9532 | 0.9165 |
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+ | 0.1613 | 2.0 | 1564 | 0.2596 | 0.9203 | 0.9274 | 0.9117 | 0.9195 |
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+ | 0.0991 | 3.0 | 2346 | 0.3105 | 0.9207 | 0.9131 | 0.9296 | 0.9213 |
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  ### Framework versions
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