---
library_name: transformers
license: mit
base_model: microsoft/speecht5_asr
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: speecht5-tunis_finalll
  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. -->

# speecht5-tunis_finalll

This model is a fine-tuned version of [microsoft/speecht5_asr](https://huggingface.co/microsoft/speecht5_asr) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2003
- Wer Ortho: 62.9526
- Wer: 59.7855

## 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-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      | Wer Ortho |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|
| 1.7381        | 0.3731 | 100  | 1.4437          | 213.9108 | 371.3889  |
| 0.8437        | 0.7463 | 200  | 0.5686          | 81.6273  | 80.5556   |
| 0.4461        | 1.1194 | 300  | 0.3668          | 77.4278  | 76.1111   |
| 0.3753        | 1.4925 | 400  | 0.2760          | 74.0157  | 72.7778   |
| 0.3416        | 1.8657 | 500  | 0.2392          | 84.7769  | 80.8333   |
| 0.2656        | 2.2388 | 600  | 0.2138          | 67.9790  | 67.7778   |
| 0.2706        | 2.6119 | 700  | 0.2085          | 77.1654  | 74.7222   |
| 0.2509        | 2.9851 | 800  | 0.1995          | 62.2047  | 63.0556   |
| 0.2314        | 3.3582 | 900  | 0.1949          | 61.6798  | 62.5      |
| 0.2806        | 3.7313 | 1000 | 0.1951          | 62.4672  | 63.3333   |
| 0.2254        | 4.1045 | 1100 | 0.1912          | 68.6111  | 69.2913   |
| 0.2674        | 4.4776 | 1200 | 0.1863          | 68.6111  | 69.8163   |
| 0.301         | 4.8507 | 1300 | 0.1862          | 67.5     | 67.9790   |
| 0.2354        | 5.2239 | 1400 | 0.1850          | 61.1111  | 59.8425   |
| 0.2349        | 5.5970 | 1500 | 0.1851          | 67.2222  | 67.7165   |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2