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bart_qa_model

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End of training

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  1. README.md +13 -7
  2. model.safetensors +1 -1
  3. runs/Jan07_17-27-25_fad11acb78a4/events.out.tfevents.1704648448.fad11acb78a4.587.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -3,6 +3,8 @@ license: apache-2.0
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  base_model: facebook/bart-base
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: bart_qa_model
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  results: []
@@ -15,7 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2453
 
 
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  ## Model description
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@@ -34,21 +38,23 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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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 |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 250 | 1.4087 |
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- | 1.9051 | 2.0 | 500 | 1.2457 |
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- | 1.9051 | 3.0 | 750 | 1.2453 |
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  ### Framework versions
 
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  base_model: facebook/bart-base
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - f1
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  model-index:
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  - name: bart_qa_model
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  results: []
 
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  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1504
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+ - F1: 0.7493
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+ - Exact Match: 0.608
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3.7185140364032e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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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 | F1 | Exact Match |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|
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+ | 2.4874 | 1.0 | 125 | 1.2569 | 0.6897 | 0.545 |
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+ | 1.1954 | 2.0 | 250 | 1.1084 | 0.7424 | 0.6 |
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+ | 0.904 | 3.0 | 375 | 1.1504 | 0.7493 | 0.608 |
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  ### Framework versions
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