---
library_name: transformers
license: mit
base_model: dawid511/speecht5_finetuned_librispeech_polish_epo6_batch2_gas4
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_librispeech_polish_epo6_batch4_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_epo6_batch4_gas2

This model is a fine-tuned version of [dawid511/speecht5_finetuned_librispeech_polish_epo6_batch2_gas4](https://huggingface.co/dawid511/speecht5_finetuned_librispeech_polish_epo6_batch2_gas4) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3653

## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7593        | 0.5115 | 100  | 0.3747          |
| 0.786         | 1.0205 | 200  | 0.3787          |
| 0.7781        | 1.5320 | 300  | 0.3732          |
| 0.767         | 2.0409 | 400  | 0.3830          |
| 0.7654        | 2.5524 | 500  | 0.3753          |
| 0.7471        | 3.0614 | 600  | 0.3697          |
| 0.7531        | 3.5729 | 700  | 0.3672          |
| 0.7365        | 4.0818 | 800  | 0.3716          |
| 0.7385        | 4.5934 | 900  | 0.3674          |
| 0.7218        | 5.1023 | 1000 | 0.3692          |
| 0.7326        | 5.6138 | 1100 | 0.3653          |


### Framework versions

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