---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f7
  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. -->

# wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f7

This model is a fine-tuned version of [facebook/wav2vec2-lv-60-espeak-cv-ft](https://huggingface.co/facebook/wav2vec2-lv-60-espeak-cv-ft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2194
- Per: 0.2658

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Per    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 17.6605       | 0.7194  | 400   | 4.5622          | 0.9860 |
| 4.3982        | 1.4388  | 800   | 4.0924          | 0.9860 |
| 4.0852        | 2.1583  | 1200  | 3.6801          | 0.9860 |
| 3.289         | 2.8777  | 1600  | 1.5881          | 0.4300 |
| 2.0883        | 3.5971  | 2000  | 0.8783          | 0.3427 |
| 1.6008        | 4.3165  | 2400  | 0.6054          | 0.3077 |
| 1.3534        | 5.0360  | 2800  | 0.4754          | 0.2917 |
| 1.2201        | 5.7554  | 3200  | 0.4041          | 0.2852 |
| 1.1139        | 6.4748  | 3600  | 0.3566          | 0.2813 |
| 1.0303        | 7.1942  | 4000  | 0.3300          | 0.2768 |
| 0.9654        | 7.9137  | 4400  | 0.3140          | 0.2749 |
| 0.9383        | 8.6331  | 4800  | 0.2941          | 0.2740 |
| 0.8962        | 9.3525  | 5200  | 0.2812          | 0.2733 |
| 0.8665        | 10.0719 | 5600  | 0.2777          | 0.2725 |
| 0.8579        | 10.7914 | 6000  | 0.2695          | 0.2707 |
| 0.8512        | 11.5108 | 6400  | 0.2628          | 0.2712 |
| 0.8363        | 12.2302 | 6800  | 0.2579          | 0.2714 |
| 0.791         | 12.9496 | 7200  | 0.2485          | 0.2699 |
| 0.7716        | 13.6691 | 7600  | 0.2472          | 0.2689 |
| 0.7773        | 14.3885 | 8000  | 0.2409          | 0.2692 |
| 0.7443        | 15.1079 | 8400  | 0.2438          | 0.2693 |
| 0.736         | 15.8273 | 8800  | 0.2395          | 0.2685 |
| 0.7459        | 16.5468 | 9200  | 0.2381          | 0.2686 |
| 0.7273        | 17.2662 | 9600  | 0.2420          | 0.2700 |
| 0.711         | 17.9856 | 10000 | 0.2347          | 0.2689 |
| 0.6997        | 18.7050 | 10400 | 0.2348          | 0.2682 |
| 0.6989        | 19.4245 | 10800 | 0.2315          | 0.2682 |
| 0.7056        | 20.1439 | 11200 | 0.2310          | 0.2669 |
| 0.6756        | 20.8633 | 11600 | 0.2304          | 0.2676 |
| 0.6873        | 21.5827 | 12000 | 0.2304          | 0.2682 |
| 0.6999        | 22.3022 | 12400 | 0.2250          | 0.2671 |
| 0.6735        | 23.0216 | 12800 | 0.2232          | 0.2672 |
| 0.6835        | 23.7410 | 13200 | 0.2229          | 0.2671 |
| 0.6648        | 24.4604 | 13600 | 0.2202          | 0.2655 |
| 0.6612        | 25.1799 | 14000 | 0.2199          | 0.2658 |
| 0.6477        | 25.8993 | 14400 | 0.2215          | 0.2669 |
| 0.6389        | 26.6187 | 14800 | 0.2217          | 0.2658 |
| 0.6742        | 27.3381 | 15200 | 0.2206          | 0.2663 |
| 0.6299        | 28.0576 | 15600 | 0.2208          | 0.2664 |
| 0.6369        | 28.7770 | 16000 | 0.2207          | 0.2661 |
| 0.6458        | 29.4964 | 16400 | 0.2194          | 0.2658 |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.1+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2