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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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metrics: |
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- accuracy |
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model-index: |
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- name: roberta_base_amazon |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# roberta_base_amazon |
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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: 0.6847 |
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- Accuracy: 0.8057 |
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- F1 Macro: 0.7452 |
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- F1 Micro: 0.8057 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 64 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:| |
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| 2.0556 | 0.26 | 50 | 1.7788 | 0.6166 | 0.4632 | 0.6166 | |
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| 1.2395 | 0.53 | 100 | 1.1504 | 0.7141 | 0.6033 | 0.7141 | |
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| 0.9724 | 0.79 | 150 | 0.9645 | 0.7385 | 0.6450 | 0.7385 | |
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| 0.8878 | 1.05 | 200 | 0.8704 | 0.7734 | 0.7001 | 0.7734 | |
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| 0.7261 | 1.32 | 250 | 0.8159 | 0.7767 | 0.7188 | 0.7767 | |
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| 0.8083 | 1.58 | 300 | 0.7718 | 0.7879 | 0.7241 | 0.7879 | |
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| 0.7209 | 1.84 | 350 | 0.7307 | 0.7997 | 0.7414 | 0.7997 | |
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| 0.6535 | 2.11 | 400 | 0.7205 | 0.8043 | 0.7452 | 0.8043 | |
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| 0.6283 | 2.37 | 450 | 0.7047 | 0.8090 | 0.7498 | 0.8090 | |
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| 0.5214 | 2.63 | 500 | 0.6879 | 0.8109 | 0.7541 | 0.8109 | |
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| 0.5808 | 2.89 | 550 | 0.6847 | 0.8057 | 0.7452 | 0.8057 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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