---
library_name: transformers
language:
- ja
license: apache-2.0
base_model: utakumi/Hubert-common_voice-phoneme-ctc_zero_infinity
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_13_0
- generated_from_trainer
datasets:
- common_voice_13_0
model-index:
- name: Hubert-ft-eval
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Hubert-ft-eval

This model is a fine-tuned version of [utakumi/Hubert-common_voice-phoneme-ctc_zero_infinity](https://huggingface.co/utakumi/Hubert-common_voice-phoneme-ctc_zero_infinity) on the MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - JA dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.6036
- eval_model_preparation_time: 0.0038
- eval_wer: 1.0
- eval_cer: 0.1999
- eval_runtime: 205.0868
- eval_samples_per_second: 24.18
- eval_steps_per_second: 3.023
- 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