wav2vec2-base-checkpoint-9
This model is a fine-tuned version of jiobiala24/wav2vec2-base-checkpoint-8 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.9203
- Wer: 0.3258
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2783 | 1.58 | 1000 | 0.5610 | 0.3359 |
0.2251 | 3.16 | 2000 | 0.5941 | 0.3374 |
0.173 | 4.74 | 3000 | 0.6026 | 0.3472 |
0.1475 | 6.32 | 4000 | 0.6750 | 0.3482 |
0.1246 | 7.9 | 5000 | 0.6673 | 0.3414 |
0.1081 | 9.48 | 6000 | 0.7072 | 0.3409 |
0.1006 | 11.06 | 7000 | 0.7413 | 0.3392 |
0.0879 | 12.64 | 8000 | 0.7831 | 0.3394 |
0.0821 | 14.22 | 9000 | 0.7371 | 0.3333 |
0.0751 | 15.8 | 10000 | 0.8321 | 0.3445 |
0.0671 | 17.38 | 11000 | 0.8362 | 0.3357 |
0.0646 | 18.96 | 12000 | 0.8709 | 0.3367 |
0.0595 | 20.54 | 13000 | 0.8352 | 0.3321 |
0.0564 | 22.12 | 14000 | 0.8854 | 0.3323 |
0.052 | 23.7 | 15000 | 0.9031 | 0.3315 |
0.0485 | 25.28 | 16000 | 0.9171 | 0.3278 |
0.046 | 26.86 | 17000 | 0.9390 | 0.3254 |
0.0438 | 28.44 | 18000 | 0.9203 | 0.3258 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
- Downloads last month
- 0
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.