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--- |
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license: mit |
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base_model: roberta-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: temp_model_outputdir |
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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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# temp_model_outputdir |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3571 |
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- Precision: 0.9390 |
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- Recall: 0.9355 |
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- F1: 0.9315 |
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- Accuracy: 0.9355 |
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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: 2.2e-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: cosine |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:| |
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| 1.9118 | 1.0 | 1511 | 0.8173 | 0.8042 | 0.7125 | 0.8320 | 0.8173 | |
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| 0.6271 | 2.0 | 3022 | 0.8402 | 0.8360 | 0.6493 | 0.8535 | 0.8402 | |
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| 0.5214 | 3.0 | 4533 | 0.8342 | 0.8285 | 0.7902 | 0.8391 | 0.8342 | |
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| 0.7385 | 4.0 | 6044 | 0.8769 | 0.8724 | 0.5748 | 0.8879 | 0.8769 | |
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| 0.6674 | 5.0 | 7555 | 0.8640 | 0.8602 | 0.5157 | 0.8802 | 0.8640 | |
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| 0.4279 | 6.0 | 9066 | 0.9077 | 0.9029 | 0.4802 | 0.9148 | 0.9077 | |
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| 0.5507 | 7.0 | 10577 | 0.3693 | 0.9371 | 0.9332 | 0.9288 | 0.9332 | |
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| 0.2703 | 8.0 | 12088 | 0.3571 | 0.9390 | 0.9355 | 0.9315 | 0.9355 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
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