---
library_name: transformers
base_model: Mehrdad-S/common_voice_clone
tags:
- generated_from_trainer
model-index:
- name: common_voice_clone_continued
  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. -->

# common_voice_clone_continued

This model is a fine-tuned version of [Mehrdad-S/common_voice_clone](https://huggingface.co/Mehrdad-S/common_voice_clone) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4442

## 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-06
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.4885        | 0.4002  | 100  | 0.4510          |
| 0.486         | 0.8004  | 200  | 0.4516          |
| 0.4836        | 1.2041  | 300  | 0.4500          |
| 0.4803        | 1.6043  | 400  | 0.4493          |
| 0.4873        | 2.0080  | 500  | 0.4510          |
| 0.4833        | 2.4082  | 600  | 0.4495          |
| 0.4869        | 2.8084  | 700  | 0.4486          |
| 0.4802        | 3.2121  | 800  | 0.4488          |
| 0.4758        | 3.6123  | 900  | 0.4470          |
| 0.4879        | 4.0160  | 1000 | 0.4472          |
| 0.4825        | 4.4162  | 1100 | 0.4480          |
| 0.4727        | 4.8164  | 1200 | 0.4457          |
| 0.4777        | 5.2201  | 1300 | 0.4485          |
| 0.4854        | 5.6203  | 1400 | 0.4488          |
| 0.4881        | 6.0240  | 1500 | 0.4472          |
| 0.481         | 6.4242  | 1600 | 0.4472          |
| 0.474         | 6.8244  | 1700 | 0.4471          |
| 0.4836        | 7.2281  | 1800 | 0.4468          |
| 0.4852        | 7.6283  | 1900 | 0.4480          |
| 0.479         | 8.0320  | 2000 | 0.4449          |
| 0.4805        | 8.4322  | 2100 | 0.4463          |
| 0.4743        | 8.8324  | 2200 | 0.4477          |
| 0.4792        | 9.2361  | 2300 | 0.4473          |
| 0.475         | 9.6363  | 2400 | 0.4451          |
| 0.4878        | 10.0400 | 2500 | 0.4456          |
| 0.478         | 10.4402 | 2600 | 0.4461          |
| 0.4805        | 10.8404 | 2700 | 0.4453          |
| 0.4773        | 11.2441 | 2800 | 0.4459          |
| 0.48          | 11.6443 | 2900 | 0.4453          |
| 0.479         | 12.0480 | 3000 | 0.4448          |
| 0.475         | 12.4482 | 3100 | 0.4437          |
| 0.4752        | 12.8484 | 3200 | 0.4461          |
| 0.4767        | 13.2521 | 3300 | 0.4434          |
| 0.4739        | 13.6523 | 3400 | 0.4458          |
| 0.4762        | 14.0560 | 3500 | 0.4431          |
| 0.4722        | 14.4562 | 3600 | 0.4450          |
| 0.4742        | 14.8564 | 3700 | 0.4442          |
| 0.4809        | 15.2601 | 3800 | 0.4448          |
| 0.475         | 15.6603 | 3900 | 0.4457          |
| 0.4789        | 16.0640 | 4000 | 0.4454          |
| 0.4709        | 16.4642 | 4100 | 0.4450          |
| 0.4826        | 16.8644 | 4200 | 0.4454          |
| 0.4735        | 17.2681 | 4300 | 0.4446          |
| 0.4727        | 17.6683 | 4400 | 0.4433          |
| 0.4867        | 18.0720 | 4500 | 0.4450          |
| 0.4804        | 18.4722 | 4600 | 0.4427          |
| 0.4802        | 18.8724 | 4700 | 0.4448          |
| 0.4798        | 19.2761 | 4800 | 0.4459          |
| 0.4788        | 19.6763 | 4900 | 0.4438          |
| 0.4772        | 20.0800 | 5000 | 0.4442          |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0