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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v2_lv_60
  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-large-v2_lv_60

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8488
- Wer: 40.1058

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 6.7165        | 1.2594 | 1000 | 0.5753          | 48.6640 |
| 4.5588        | 2.5189 | 2000 | 0.5946          | 39.7174 |
| 3.1389        | 3.7783 | 3000 | 0.6317          | 41.1180 |
| 1.1761        | 5.0378 | 4000 | 0.7433          | 39.6426 |
| 1.0312        | 6.2972 | 5000 | 0.7913          | 39.5923 |
| 0.9134        | 7.5567 | 6000 | 0.8488          | 40.1058 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0