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finetuning-sentiment-model-5000-samples

Text Classification
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distilbert
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  1. README.md +8 -12
  2. model.safetensors +1 -1
  3. runs/Jun14_01-37-57_88b985c19838/events.out.tfevents.1718329078.88b985c19838.1237.26 +2 -2
  4. runs/Jun14_01-37-57_88b985c19838/events.out.tfevents.1718329631.88b985c19838.1237.27 +3 -0
README.md CHANGED
@@ -18,9 +18,9 @@ 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-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6864
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- - Accuracy: 0.9178
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- - F1: 0.9453
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  ## Model description
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@@ -45,18 +45,14 @@ 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: 6
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | No log | 1.0 | 254 | 0.5507 | 0.9178 | 0.9463 |
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- | 0.0173 | 2.0 | 508 | 0.7152 | 0.8978 | 0.9313 |
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- | 0.0173 | 3.0 | 762 | 0.7228 | 0.9111 | 0.9420 |
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- | 0.0117 | 4.0 | 1016 | 0.7015 | 0.9044 | 0.9361 |
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- | 0.0117 | 5.0 | 1270 | 0.6796 | 0.9111 | 0.9417 |
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- | 0.0075 | 6.0 | 1524 | 0.6864 | 0.9178 | 0.9453 |
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  ### Framework versions
 
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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 None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9372
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+ - Accuracy: 0.9133
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+ - F1: 0.9419
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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: 4
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
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+ | 0.006 | 1.9685 | 500 | 0.9543 | 0.9133 | 0.9434 |
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+ | 0.0019 | 3.9370 | 1000 | 0.9404 | 0.9133 | 0.9419 |
 
 
 
 
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  ### Framework versions
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