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---
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license: apache-2.0
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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: M_gpt_v1.3
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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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# M_gpt_v1.3
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This model is a fine-tuned version of [ai-forever/mGPT](https://huggingface.co/ai-forever/mGPT) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4547
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- Precision: 0.56
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- Recall: 0.3739
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- F1: 0.4484
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- Accuracy: 0.9076
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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: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.4869 | 1.0 | 882 | 0.3957 | 0.5886 | 0.2987 | 0.3963 | 0.8995 |
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| 0.3467 | 2.0 | 1764 | 0.3723 | 0.5572 | 0.3696 | 0.4444 | 0.9033 |
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| 0.3031 | 3.0 | 2646 | 0.3709 | 0.5917 | 0.3289 | 0.4228 | 0.9082 |
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| 0.2786 | 4.0 | 3528 | 0.3928 | 0.5649 | 0.3760 | 0.4515 | 0.9069 |
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| 0.2629 | 5.0 | 4410 | 0.4547 | 0.56 | 0.3739 | 0.4484 | 0.9076 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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