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---
library_name: transformers
license: apache-2.0
base_model: mouseyy/result_data-1
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: result_data_2-2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: uk
split: test
args: uk
metrics:
- name: Wer
type: wer
value: 0.34786300594395697
---
<!-- 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. -->
# result_data_2-2
This model is a fine-tuned version of [mouseyy/result_data-1](https://huggingface.co/mouseyy/result_data-1) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2338
- Wer: 0.3479
- Cer: 0.1661
## 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: 1.3065956368514577e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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: 184
- num_epochs: 5.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 0.1695 | 0.9099 | 1000 | 0.2457 | 0.3725 | 0.1714 |
| 0.1502 | 1.8198 | 2000 | 0.2344 | 0.3640 | 0.1704 |
| 0.1287 | 2.7298 | 3000 | 0.2321 | 0.3617 | 0.1691 |
| 0.1248 | 3.6397 | 4000 | 0.2387 | 0.3561 | 0.1665 |
| 0.1127 | 4.5496 | 5000 | 0.2371 | 0.3493 | 0.1667 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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