---
library_name: transformers
license: apache-2.0
base_model: tmtms/whisper_checkpoints
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_checkpoints7
  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. -->

# whisper_checkpoints7

This model is a fine-tuned version of [tmtms/whisper_checkpoints](https://huggingface.co/tmtms/whisper_checkpoints) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0170
- Wer: 20.9137

## 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: 1e-05
- train_batch_size: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.009         | 2.5510  | 1000 | 0.0306          | 21.4887 |
| 0.0011        | 5.1020  | 2000 | 0.0184          | 22.1210 |
| 0.0005        | 7.6531  | 3000 | 0.0172          | 21.3229 |
| 0.0004        | 10.2041 | 4000 | 0.0170          | 20.9137 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0