anuragshas/wav2vec2-xls-r-300m-mr-cv9-with-lm

🤗 Hugging Face 来源automatic-speech-recognitionapache-2.022 GBother✓ 4 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo anuragshas/wav2vec2-xls-r-300m-mr-cv9-with-lm ./model-folder
需要做种者 →

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - MR dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3642
  • Wer: 0.4190
  • Cer: 0.0946

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: 7.5e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 6124
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
3.5184 12.9 400 3.4210 1.0 1.0
2.3797 25.81 800 1.1068 0.8389 0.2584
1.5022 38.71 1200 0.5278 0.6280 0.1517
1.3181 51.61 1600 0.4254 0.5587 0.1297
1.2037 64.52 2000 0.3836 0.5143 0.1176
1.1245 77.42 2400 0.3643 0.4871 0.1111
1.0582 90.32 2800 0.3562 0.4676 0.1062
1.0027 103.23 3200 0.3530 0.4625 0.1058
0.9382 116.13 3600 0.3388 0.4442 0.1002
0.8915 129.03 4000 0.3430 0.4427 0.1000
0.853 141.94 4400 0.3536 0.4375 0.1000
0.8127 154.84 4800 0.3511 0.4344 0.0986
0.7861 167.74 5200 0.3595 0.4372 0.0993
0.7619 180.65 5600 0.3628 0.4316 0.0985
0.7537 193.55 6000 0.3633 0.4174 0.0943

Framework versions

  • Transformers 4.19.0.dev0
  • Pytorch 1.11.0+cu102
  • Datasets 2.1.1.dev0
  • Tokenizers 0.12.1