---
library_name: transformers
license: mit
base_model: jhu-clsp/mmBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trainer_output
  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. -->

# trainer_output

This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4158
- Accuracy: 94.7892
- Sentence accuracy: 54.4954

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Sentence accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|
| 0.7863        | 1.0   | 546  | 0.3676          | 90.7489  | 37.6147           |
| 0.2408        | 2.0   | 1092 | 0.2598          | 93.2662  | 47.3394           |
| 0.1363        | 3.0   | 1638 | 0.2659          | 93.6060  | 47.7064           |
| 0.0828        | 4.0   | 2184 | 0.2874          | 94.2857  | 51.0092           |
| 0.0525        | 5.0   | 2730 | 0.3354          | 94.1221  | 50.0917           |
| 0.0321        | 6.0   | 3276 | 0.3410          | 94.4242  | 53.5780           |
| 0.0206        | 7.0   | 3822 | 0.3864          | 94.4619  | 51.7431           |
| 0.0161        | 8.0   | 4368 | 0.3735          | 94.8143  | 53.5780           |
| 0.0101        | 9.0   | 4914 | 0.3780          | 94.9654  | 55.4128           |
| 0.0089        | 10.0  | 5460 | 0.3959          | 94.6130  | 53.3945           |
| 0.0055        | 11.0  | 6006 | 0.4154          | 94.8018  | 53.3945           |
| 0.0046        | 12.0  | 6552 | 0.4089          | 94.8899  | 54.6789           |
| 0.0041        | 13.0  | 7098 | 0.4007          | 95.1542  | 55.2294           |
| 0.0028        | 14.0  | 7644 | 0.4057          | 95.0535  | 55.5963           |
| 0.0019        | 15.0  | 8190 | 0.4216          | 95.0157  | 54.3119           |
| 0.0021        | 16.0  | 8736 | 0.4158          | 95.0913  | 56.3303           |
| 0.0027        | 17.0  | 9282 | 0.4158          | 94.7892  | 54.4954           |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2