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---
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
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