---
library_name: transformers
license: apache-2.0
base_model: biodatlab/whisper-th-small-combined
tags:
- generated_from_trainer
model-index:
- name: outs
  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. -->

# outs

This model is a fine-tuned version of [biodatlab/whisper-th-small-combined](https://huggingface.co/biodatlab/whisper-th-small-combined) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1631
- Cer: 10.9836

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2.0
- total_train_batch_size: 32.0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| No log        | 0.9926 | 67   | 0.1876          | 10.2687 |
| 0.1249        | 2.0    | 135  | 0.1632          | 13.0653 |
| 0.0715        | 2.9926 | 202  | 0.1870          | 14.0862 |
| 0.0715        | 4.0    | 270  | 0.1636          | 10.3119 |
| 0.0386        | 4.9630 | 335  | 0.1631          | 10.9836 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1