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v2-wav2vec2-large-xls-r-300m-french-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.3972
- Wer: 0.2154
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.3672 | 1.07 | 400 | 0.4010 | 0.3241 |
0.3467 | 2.14 | 800 | 0.4687 | 0.3642 |
0.3223 | 3.21 | 1200 | 0.4495 | 0.3248 |
0.3236 | 4.28 | 1600 | 0.4325 | 0.3289 |
0.2764 | 5.35 | 2000 | 0.4101 | 0.3005 |
0.2554 | 6.42 | 2400 | 0.4211 | 0.3148 |
0.2198 | 7.49 | 2800 | 0.4217 | 0.2946 |
0.2112 | 8.56 | 3200 | 0.4217 | 0.2930 |
0.1813 | 9.63 | 3600 | 0.4110 | 0.2682 |
0.1727 | 10.7 | 4000 | 0.3908 | 0.2791 |
0.1543 | 11.76 | 4400 | 0.4284 | 0.2746 |
0.154 | 12.83 | 4800 | 0.4096 | 0.2743 |
0.134 | 13.9 | 5200 | 0.4157 | 0.2582 |
0.1207 | 14.97 | 5600 | 0.4057 | 0.2525 |
0.1145 | 16.04 | 6000 | 0.4255 | 0.2498 |
0.0996 | 17.11 | 6400 | 0.4282 | 0.2488 |
0.0971 | 18.18 | 6800 | 0.3763 | 0.2427 |
0.0886 | 19.25 | 7200 | 0.3833 | 0.2473 |
0.082 | 20.32 | 7600 | 0.3849 | 0.2402 |
0.0765 | 21.39 | 8000 | 0.4083 | 0.2327 |
0.07 | 22.46 | 8400 | 0.4132 | 0.2355 |
0.0601 | 23.53 | 8800 | 0.4124 | 0.2332 |
0.0583 | 24.6 | 9200 | 0.3956 | 0.2248 |
0.0537 | 25.67 | 9600 | 0.4103 | 0.2289 |
0.0487 | 26.74 | 10000 | 0.4050 | 0.2266 |
0.0459 | 27.81 | 10400 | 0.3827 | 0.2173 |
0.0426 | 28.88 | 10800 | 0.3943 | 0.2152 |
0.0386 | 29.95 | 11200 | 0.3972 | 0.2154 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2