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# bert-emotion

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1060
- Precision: 0.7250
- Recall: 0.7243
- Fscore: 0.7225

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.8399        | 1.0   | 815  | 0.6333          | 0.7495    | 0.7146 | 0.7265 |
| 0.5379        | 2.0   | 1630 | 0.8113          | 0.7660    | 0.7188 | 0.7357 |
| 0.2567        | 3.0   | 2445 | 1.1060          | 0.7250    | 0.7243 | 0.7225 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["tweet_eval"], "metrics": ["precision", "recall"], "base_model": "distilbert-base-cased", "model-index": [{"name": "bert-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "tweet_eval", "type": "tweet_eval", "config": "emotion", "split": "validation", "args": "emotion"}, "metrics": [{"type": "precision", "value": 0.7250217383862243, "name": "Precision"}, {"type": "recall", "value": 0.7243162915142891, "name": "Recall"}]}]}]}
transformers safetensors distilbert text-classification generated_from_trainer dataset:tweet_eval base_model:distilbert-base-cased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us