metadata

license: cc-by-nc-4.0
base_model: facebook/mms-1b-fl102
tags:
  - generated_from_trainer
datasets:
  - common_voice_6_1
metrics:
  - wer
model-index:
  - name: wav2vec2-large-mms-1b-hindi-colab
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_6_1
          type: common_voice_6_1
          config: hi
          split: test
          args: hi
        metrics:
          - name: Wer
            type: wer
            value: 0.32018561484918795

wav2vec2-large-mms-1b-hindi-colab

This model is a fine-tuned version of facebook/mms-1b-fl102 on the common_voice_6_1 dataset. It achieves the following results on the evaluation set:

Loss: 0.3535
Wer: 0.3202

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: 0.001
train_batch_size: 4
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: 10
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
16.7585	0.14	10	10.2106	2.0951
6.9602	0.27	20	3.7700	1.0046
2.4653	0.41	30	1.3321	0.6763
1.0919	0.55	40	0.6594	0.4664
0.7645	0.68	50	0.4930	0.3910
0.8434	0.82	60	0.4819	0.3898
0.5118	0.96	70	0.4492	0.3817
0.6097	1.1	80	0.4299	0.4327
0.4698	1.23	90	0.4308	0.3643
0.5402	1.37	100	0.4042	0.4107
0.5622	1.51	110	0.4156	0.3701
0.4084	1.64	120	0.4138	0.3701
0.4888	1.78	130	0.3917	0.3434
0.4253	1.92	140	0.3852	0.3457
0.5004	2.05	150	0.3843	0.3364
0.3791	2.19	160	0.3841	0.3469
0.3302	2.33	170	0.3764	0.3271
0.4047	2.47	180	0.3689	0.3364
0.2951	2.6	190	0.3657	0.3329
0.3545	2.74	200	0.3582	0.3306
0.3736	2.88	210	0.3585	0.3248
0.388	3.01	220	0.3602	0.3237
0.2997	3.15	230	0.3624	0.3167
0.3704	3.29	240	0.3625	0.3190
0.2095	3.42	250	0.3571	0.3248
0.3564	3.56	260	0.3570	0.3202
0.2119	3.7	270	0.3550	0.3225
0.3697	3.84	280	0.3542	0.3190
0.3551	3.97	290	0.3535	0.3202

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3