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

# translation-source-classifier

This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5460
- Accuracy: 0.6111

## 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: 0.001
- train_batch_size: 128
- eval_batch_size: 128
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.1867        | 1.0   | 14063  | 2.2778          | 0.4457   |
| 2.0165        | 2.0   | 28126  | 2.0671          | 0.4984   |
| 1.935         | 3.0   | 42189  | 1.9881          | 0.5151   |
| 1.8636        | 4.0   | 56252  | 1.8941          | 0.5351   |
| 1.7705        | 5.0   | 70315  | 1.8231          | 0.5460   |
| 1.7174        | 6.0   | 84378  | 1.7304          | 0.5691   |
| 1.6526        | 7.0   | 98441  | 1.6755          | 0.5788   |
| 1.6009        | 8.0   | 112504 | 1.6174          | 0.5922   |
| 1.4959        | 9.0   | 126567 | 1.5779          | 0.6025   |
| 1.4539        | 10.0  | 140630 | 1.5460          | 0.6111   |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2