metadata
library_name: transformers
language:
- zh
base_model: whucedar/amoros_spec_01_train_20-medium_1000_8
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- whucedar/amoros_spec_02-medium
metrics:
- wer
model-index:
- name: amoros_spec_02-medium
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: amoros_spec_02
type: whucedar/amoros_spec_02-medium
args: 'config: zh, split: test'
metrics:
- name: Wer
type: wer
value: 438.75
amoros_spec_02-medium
This model is a fine-tuned version of whucedar/amoros_spec_01_train_20-medium_1000_8 on the amoros_spec_02 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5581
- Wer: 438.75
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
- optimizer: Use OptimizerNames.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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0001 | 100.0 | 1000 | 0.5581 | 438.75 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1