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--- |
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license: mit |
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base_model: xlnet/xlnet-base-cased |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: emotional-xlnet |
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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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# emotional-xlnet |
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This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.9968 |
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- Accuracy: 0.3875 |
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- F1: 0.3676 |
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- Precision: 0.3990 |
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- Recall: 0.3875 |
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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: 16 |
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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: 10 |
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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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| 2.4746 | 1.0 | 270 | 2.3530 | 0.3085 | 0.2878 | 0.4138 | 0.3085 | |
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| 0.8581 | 2.0 | 540 | 2.1600 | 0.3466 | 0.3310 | 0.3603 | 0.3466 | |
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| 0.2628 | 3.0 | 810 | 2.3594 | 0.3575 | 0.3519 | 0.4060 | 0.3575 | |
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| 0.0791 | 4.0 | 1080 | 2.7493 | 0.3793 | 0.3643 | 0.3901 | 0.3793 | |
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| 0.0292 | 5.0 | 1350 | 2.9968 | 0.3875 | 0.3676 | 0.3990 | 0.3875 | |
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### Framework versions |
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- Transformers 4.39.3 |
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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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