---
library_name: transformers
language:
- ja
license: apache-2.0
base_model: utakumi/Hubert-noisy_common_voice_debug
tags:
- automatic-speech-recognition
- original_noisy_common_voice
- generated_from_trainer
model-index:
- name: Hubert-noisy-ft-eval
  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. -->

# Hubert-noisy-ft-eval

This model is a fine-tuned version of [utakumi/Hubert-noisy_common_voice_debug](https://huggingface.co/utakumi/Hubert-noisy_common_voice_debug) on the ORIGINAL_NOISY_COMMON_VOICE - JA dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.1085
- eval_model_preparation_time: 0.0093
- eval_wer: 1.0
- eval_cer: 0.3247
- eval_runtime: 152.9105
- eval_samples_per_second: 32.444
- eval_steps_per_second: 4.061
- step: 0

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_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: cosine
- lr_scheduler_warmup_steps: 12500
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3