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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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datasets: |
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- tweet_eval |
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metrics: |
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- f1 |
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model-index: |
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- name: sentiment_trained |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: tweet_eval |
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type: tweet_eval |
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args: sentiment |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.7253452834090693 |
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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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# sentiment_trained |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2671 |
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- F1: 0.7253 |
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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: 1.2140338797769864e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 0 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.6647 | 1.0 | 11404 | 0.6424 | 0.7189 | |
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| 0.6018 | 2.0 | 22808 | 0.7947 | 0.7170 | |
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| 0.5004 | 3.0 | 34212 | 1.0811 | 0.7200 | |
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| 0.3761 | 4.0 | 45616 | 1.2671 | 0.7253 | |
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### Framework versions |
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- Transformers 4.12.5 |
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- Pytorch 1.9.1 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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