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aift-model-review-multiple-label-classification

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Cielciel/aift-model-review-multiple-label-classification_new

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Files changed (9) hide show
  1. README.md +12 -12
  2. model.safetensors +1 -1
  3. models/model.safetensors +1 -1
  4. models/training_args.bin +1 -1
  5. runs/Jan10_09-36-35_aift-review-classification-multiple-label/events.out.tfevents.1704879524.aift-review-classification-multiple-label +2 -2
  6. runs/Jan11_02-10-23_aift-review-classification-multiple-label/events.out.tfevents.1704939028.aift-review-classification-multiple-label +3 -0
  7. runs/Jan11_02-10-23_aift-review-classification-multiple-label/events.out.tfevents.1704939101.aift-review-classification-multiple-label +3 -0
  8. runs/Jan11_02-10-23_aift-review-classification-multiple-label/events.out.tfevents.1704939159.aift-review-classification-multiple-label +3 -0
  9. training_args.bin +1 -1
README.md CHANGED
@@ -15,8 +15,8 @@ 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 the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1868
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- - Accuracy Thresh: 0.9136
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  ## Model description
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@@ -48,16 +48,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy Thresh |
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  |:-------------:|:-----:|:----:|:---------------:|:---------------:|
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- | No log | 1.0 | 70 | 0.4240 | 0.7800 |
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- | No log | 2.0 | 140 | 0.3213 | 0.8507 |
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- | No log | 3.0 | 210 | 0.2606 | 0.9021 |
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- | No log | 4.0 | 280 | 0.2338 | 0.9014 |
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- | No log | 5.0 | 350 | 0.2142 | 0.9100 |
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- | No log | 6.0 | 420 | 0.2070 | 0.9043 |
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- | No log | 7.0 | 490 | 0.1974 | 0.9136 |
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- | 0.2882 | 8.0 | 560 | 0.1915 | 0.9143 |
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- | 0.2882 | 9.0 | 630 | 0.1900 | 0.9136 |
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- | 0.2882 | 10.0 | 700 | 0.1868 | 0.9136 |
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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 the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4183
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+ - Accuracy Thresh: 0.9179
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy Thresh |
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  |:-------------:|:-----:|:----:|:---------------:|:---------------:|
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+ | No log | 1.0 | 70 | 1.1564 | 0.8786 |
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+ | No log | 2.0 | 140 | 0.9926 | 0.8879 |
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+ | No log | 3.0 | 210 | 1.0794 | 0.9064 |
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+ | No log | 4.0 | 280 | 1.2496 | 0.9221 |
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+ | No log | 5.0 | 350 | 1.1574 | 0.9107 |
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+ | No log | 6.0 | 420 | 1.3792 | 0.9171 |
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+ | No log | 7.0 | 490 | 1.3086 | 0.9179 |
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+ | 0.6024 | 8.0 | 560 | 1.4221 | 0.9221 |
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+ | 0.6024 | 9.0 | 630 | 1.4423 | 0.9164 |
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+ | 0.6024 | 10.0 | 700 | 1.4183 | 0.9179 |
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  ### Framework versions
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