---
library_name: transformers
base_model: dawid511/speecht5_finetuned_librispeech_polish_epo6_batch8_gas4
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_librispeech_polish_epo10_batch2_gas2
  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_finetuned_librispeech_polish_epo10_batch2_gas2

This model is a fine-tuned version of [dawid511/speecht5_finetuned_librispeech_polish_epo6_batch8_gas4](https://huggingface.co/dawid511/speecht5_finetuned_librispeech_polish_epo6_batch8_gas4) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3637

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use 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: 100
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7279        | 0.2558 | 100  | 0.3734          |
| 0.7647        | 0.5115 | 200  | 0.3829          |
| 0.7646        | 0.7673 | 300  | 0.3793          |
| 0.7521        | 1.0230 | 400  | 0.3804          |
| 0.7673        | 1.2788 | 500  | 0.3817          |
| 0.7415        | 1.5345 | 600  | 0.3824          |
| 0.7721        | 1.7903 | 700  | 0.3960          |
| 0.7766        | 2.0460 | 800  | 0.3767          |
| 0.7529        | 2.3018 | 900  | 0.3756          |
| 0.757         | 2.5575 | 1000 | 0.3809          |
| 0.757         | 2.8133 | 1100 | 0.3808          |
| 0.746         | 3.0691 | 1200 | 0.3762          |
| 0.7424        | 3.3248 | 1300 | 0.3744          |
| 0.7409        | 3.5806 | 1400 | 0.3778          |
| 0.7453        | 3.8363 | 1500 | 0.3715          |
| 0.7409        | 4.0921 | 1600 | 0.3722          |
| 0.7441        | 4.3478 | 1700 | 0.3728          |
| 0.7304        | 4.6036 | 1800 | 0.3724          |
| 0.738         | 4.8593 | 1900 | 0.3710          |
| 0.7213        | 5.1151 | 2000 | 0.3730          |
| 0.7446        | 5.3708 | 2100 | 0.3721          |
| 0.7255        | 5.6266 | 2200 | 0.3684          |
| 0.7321        | 5.8824 | 2300 | 0.3671          |
| 0.7098        | 6.1381 | 2400 | 0.3673          |
| 0.7401        | 6.3939 | 2500 | 0.3735          |
| 0.7165        | 6.6496 | 2600 | 0.3679          |
| 0.714         | 6.9054 | 2700 | 0.3733          |
| 0.7035        | 7.1611 | 2800 | 0.3666          |
| 0.7089        | 7.4169 | 2900 | 0.3689          |
| 0.7118        | 7.6726 | 3000 | 0.3691          |
| 0.7064        | 7.9284 | 3100 | 0.3664          |
| 0.6994        | 8.1841 | 3200 | 0.3679          |
| 0.6958        | 8.4399 | 3300 | 0.3661          |
| 0.7087        | 8.6957 | 3400 | 0.3683          |
| 0.6968        | 8.9514 | 3500 | 0.3635          |
| 0.7035        | 9.2072 | 3600 | 0.3647          |
| 0.7045        | 9.4629 | 3700 | 0.3647          |
| 0.6982        | 9.7187 | 3800 | 0.3642          |
| 0.6996        | 9.9744 | 3900 | 0.3637          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0