---
base_model: jiangg/chembert_cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: chembert_cased-tokenCLS-BATTERY
  results: []
---

<!-- 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. -->

# chembert_cased-tokenCLS-BATTERY

This model is a fine-tuned version of [jiangg/chembert_cased](https://huggingface.co/jiangg/chembert_cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0640
- Precision: 0.7172
- Recall: 0.8558
- F1: 0.7804
- Accuracy: 0.9794

## 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: 8
- eval_batch_size: 8
- 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 | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 338  | 0.0771          | 0.6907    | 0.7945 | 0.7389 | 0.9730   |
| 0.1448        | 2.0   | 676  | 0.0617          | 0.6957    | 0.8344 | 0.7587 | 0.9777   |
| 0.0477        | 3.0   | 1014 | 0.0640          | 0.7172    | 0.8558 | 0.7804 | 0.9794   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3