w2v-bert-2.0-japanese-colab-CV16.0

This model is a fine-tuned version of ylacombe/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:

• Loss: inf
• Cer: 0.3171

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
4.2694	0.96	300	inf	0.6823
2.0595	1.93	600	inf	0.4528
1.3044	2.89	900	inf	0.3920
1.0889	3.85	1200	inf	0.3579
0.7867	4.82	1500	inf	0.3518
0.4371	5.78	1800	inf	0.3371
0.3414	6.74	2100	inf	0.3246
0.2373	7.7	2400	inf	0.3253
0.1171	8.67	2700	inf	0.3183
0.0524	9.63	3000	inf	0.3171

Framework versions

• Transformers 4.37.0.dev0
• Pytorch 2.1.2+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1