
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# baseline_BERT_50K_steps

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the arxiv_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0192
- Accuracy: 0.9937
- Precision: 0.7968
- Recall: 0.4734
- F1: 0.5940
- Hamming: 0.0063

## 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: 2e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 50000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.0343        | 0.03  | 10000 | 0.0315          | 0.9912   | 0.7679    | 0.1370 | 0.2326 | 0.0088  |
| 0.0244        | 0.06  | 20000 | 0.0234          | 0.9925   | 0.7813    | 0.3262 | 0.4602 | 0.0075  |
| 0.0219        | 0.09  | 30000 | 0.0210          | 0.9931   | 0.7572    | 0.4320 | 0.5502 | 0.0069  |
| 0.0204        | 0.12  | 40000 | 0.0197          | 0.9935   | 0.7738    | 0.4711 | 0.5857 | 0.0065  |
| 0.0197        | 0.15  | 50000 | 0.0192          | 0.9937   | 0.7968    | 0.4734 | 0.5940 | 0.0063  |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.12.1+cu113
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["arxiv_dataset"], "metrics": ["accuracy", "precision", "recall", "f1"], "base_model": "bert-base-uncased", "model-index": [{"name": "baseline_BERT_50K_steps", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "arxiv_dataset", "type": "arxiv_dataset", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9936787420400056, "name": "Accuracy"}, {"type": "precision", "value": 0.7967781908302355, "name": "Precision"}, {"type": "recall", "value": 0.4734468476760239, "name": "Recall"}, {"type": "f1", "value": 0.5939610876970152, "name": "F1"}]}]}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:arxiv_dataset base_model:bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us