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distilbert-qa-mash-covid

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  1. README.md +10 -17
  2. model.safetensors +1 -1
  3. runs/Jun03_01-17-26_b4bb6272339d/events.out.tfevents.1717377447.b4bb6272339d.34.0 +2 -2
  4. training_args.bin +1 -1
README.md CHANGED
@@ -1,9 +1,7 @@
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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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- - question-answering
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- - nlp
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  - generated_from_trainer
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  model-index:
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  - name: distilbert-qa-mash-covid
@@ -15,9 +13,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilbert-qa-mash-covid
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the mashqa_dataset dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6691
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  ## Model description
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@@ -42,22 +40,17 @@ 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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 1.9281 | 1.0 | 657 | 1.4079 |
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- | 1.4703 | 2.0 | 1314 | 1.2640 |
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- | 1.3062 | 3.0 | 1971 | 1.2448 |
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- | 1.0172 | 4.0 | 2628 | 1.2780 |
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- | 0.8991 | 5.0 | 3285 | 1.3009 |
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- | 0.8004 | 6.0 | 3942 | 1.4255 |
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- | 0.6502 | 7.0 | 4599 | 1.4567 |
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- | 0.5806 | 8.0 | 5256 | 1.5352 |
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- | 0.5117 | 9.0 | 5913 | 1.6334 |
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- | 0.4538 | 10.0 | 6570 | 1.6691 |
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  ### Framework versions
 
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  ---
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+ license: mit
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+ base_model: FacebookAI/roberta-base
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  tags:
 
 
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  - generated_from_trainer
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  model-index:
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  - name: distilbert-qa-mash-covid
 
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  # distilbert-qa-mash-covid
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+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0643
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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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.6892 | 1.0 | 657 | 1.0350 |
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+ | 1.0865 | 2.0 | 1314 | 1.0145 |
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+ | 0.9423 | 3.0 | 1971 | 0.9382 |
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+ | 0.6721 | 4.0 | 2628 | 0.9880 |
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+ | 0.5998 | 5.0 | 3285 | 1.0643 |
 
 
 
 
 
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  ### Framework versions
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