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--- |
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library_name: transformers |
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license: mit |
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base_model: 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: roberta-base-sentiment |
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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-sentiment |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on a manually labelled sentiment dataset of earnings call transcript sentences. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8190 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.09 | 1.0 | 39 | 1.0853 | |
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| 1.0329 | 2.0 | 78 | 1.0255 | |
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| 0.7433 | 3.0 | 117 | 0.8066 | |
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| 0.7679 | 4.0 | 156 | 0.7961 | |
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| 0.4994 | 5.0 | 195 | 0.8190 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
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