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End of training

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  1. README.md +20 -14
  2. model.safetensors +1 -1
  3. tokenizer_config.json +7 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -1,6 +1,4 @@
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  ---
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- license: mit
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- base_model: LIAMF-USP/roberta-large-finetuned-race
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -18,13 +16,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # roberta-mqa-formrat
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- This model is a fine-tuned version of [LIAMF-USP/roberta-large-finetuned-race](https://huggingface.co/LIAMF-USP/roberta-large-finetuned-race) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6094
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- - Accuracy: 0.2075
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- - F1: 0.1943
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- - Precision: 0.2025
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- - Recall: 0.2019
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  ## Model description
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@@ -44,9 +42,11 @@ More information needed
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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: 8
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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
@@ -54,11 +54,17 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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- |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 1.6083 | 1.0 | 3712 | 1.6094 | 0.1981 | 0.1925 | 0.1939 | 0.1944 |
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- | 1.6124 | 2.0 | 7424 | 1.6094 | 0.2050 | 0.2020 | 0.2033 | 0.2030 |
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- | 1.6113 | 3.0 | 11136 | 1.6094 | 0.2075 | 0.1943 | 0.2025 | 0.2019 |
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
 
 
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # roberta-mqa-formrat
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+ This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1135
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+ - Accuracy: 0.5671
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+ - F1: 0.5659
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+ - Precision: 0.5683
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+ - Recall: 0.5650
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  ## Model description
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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: 4
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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: 8
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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 | F1 | Precision | Recall |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.451 | 0.3233 | 1200 | 1.4125 | 0.4105 | 0.4093 | 0.4151 | 0.4107 |
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+ | 1.416 | 0.6466 | 2400 | 1.3482 | 0.4412 | 0.4394 | 0.4438 | 0.4385 |
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+ | 1.3157 | 0.9698 | 3600 | 1.2933 | 0.4788 | 0.4772 | 0.4776 | 0.4773 |
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+ | 1.2616 | 1.2931 | 4800 | 1.2389 | 0.5032 | 0.5022 | 0.5053 | 0.5011 |
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+ | 1.221 | 1.6164 | 6000 | 1.2049 | 0.5053 | 0.5039 | 0.5060 | 0.5029 |
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+ | 1.1556 | 1.9397 | 7200 | 1.1792 | 0.5288 | 0.5276 | 0.5295 | 0.5265 |
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+ | 1.082 | 2.2629 | 8400 | 1.1593 | 0.5451 | 0.5434 | 0.5487 | 0.5415 |
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+ | 1.0692 | 2.5862 | 9600 | 1.1153 | 0.5613 | 0.5606 | 0.5641 | 0.5594 |
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+ | 1.0066 | 2.9095 | 10800 | 1.1135 | 0.5671 | 0.5659 | 0.5683 | 0.5650 |
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  ### Framework versions
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tokenizer_config.json CHANGED
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  "eos_token": "</s>",
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  "mask_token": "<mask>",
 
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  "model_max_length": 512,
 
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  "pad_token": "<pad>",
 
 
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  "sep_token": "</s>",
 
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  "tokenizer_class": "RobertaTokenizer",
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  "trim_offsets": true,
 
 
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  "unk_token": "<unk>"
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  }
 
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  "eos_token": "</s>",
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  "errors": "replace",
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  "mask_token": "<mask>",
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+ "max_length": 128,
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  "tokenizer_class": "RobertaTokenizer",
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+ "truncation_side": "right",
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+ "truncation_strategy": "longest_first",
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  "unk_token": "<unk>"
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  }
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