
<!-- 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. -->

# concepts-finetuned-bert

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8103
- Accuracy: 0.5181
- F1: 0.4759
- Randombaseline accuracy: 0.0092
- Baseline accuracy: 0.1526

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Randombaseline accuracy | Baseline accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-----------------------:|:-----------------:|
| 3.064         | 2.47  | 400  | 2.6742          | 0.3381   | 0.2679 | 0.0143                  | 0.15              |
| 2.4288        | 4.94  | 800  | 2.3136          | 0.4028   | 0.3468 | 0.0098                  | 0.1487            |
| 2.2341        | 7.41  | 1200 | 2.1213          | 0.4378   | 0.3928 | 0.0050                  | 0.1452            |
| 2.0898        | 9.88  | 1600 | 1.9961          | 0.4602   | 0.4141 | 0.0123                  | 0.1424            |
| 1.9711        | 12.35 | 2000 | 1.9365          | 0.4844   | 0.4387 | 0.0092                  | 0.1394            |
| 1.9357        | 14.81 | 2400 | 1.8505          | 0.4915   | 0.4504 | 0.0051                  | 0.1469            |
| 1.8361        | 17.28 | 2800 | 1.9046          | 0.4975   | 0.4535 | 0.0089                  | 0.1495            |
| 1.8127        | 19.75 | 3200 | 1.8790          | 0.4898   | 0.4401 | 0.0082                  | 0.1565            |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "concepts-finetuned-bert", "results": []}]}
transformers tensorboard safetensors bert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us