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---
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
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