---
license: apache-2.0
base_model: honzapucalek/hc-czech-large-v3-v2-independent
tags:
- generated_from_trainer
datasets:
- honzapucalek/impaired_v3_independent_all
metrics:
- wer
model-index:
- name: impaired-v3-independent-all-hc-train
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: honzapucalek/impaired_v3_independent_all cs
      type: honzapucalek/impaired_v3_independent_all
      config: cs
      split: test
      args: cs
    metrics:
    - name: Wer
      type: wer
      value: 0.4058704453441296
---

<!-- 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. -->

# impaired-v3-independent-all-hc-train

This model is a fine-tuned version of [honzapucalek/hc-czech-large-v3-v2-independent](https://huggingface.co/honzapucalek/hc-czech-large-v3-v2-independent) on the honzapucalek/impaired_v3_independent_all cs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4176
- Wer: 0.4059

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.006         | 13.99 | 1000 | 1.1860          | 0.4332 |
| 0.0022        | 27.97 | 2000 | 1.1733          | 0.4211 |
| 0.0001        | 41.96 | 3000 | 1.3533          | 0.4109 |
| 0.0           | 55.94 | 4000 | 1.4029          | 0.4099 |
| 0.0           | 69.93 | 5000 | 1.4176          | 0.4059 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1