README.md

metadata

license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - wer
model-index:
  - name: wav2vec2-mms-1b-all-swc-kat6
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: train
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 0.37098445595854923

wav2vec2-mms-1b-all-swc-kat6

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

• Loss: inf
• Wer: 0.3710

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: 1
• 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: 400
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.8349	0.07	400	inf	0.4899
0.8039	0.15	800	inf	0.4912
0.7335	0.22	1200	inf	0.4482
0.8395	0.3	1600	inf	0.4829
0.7626	0.37	2000	inf	0.4635
0.9035	0.44	2400	inf	0.4391
0.6281	0.52	2800	inf	0.4668
0.6756	0.59	3200	inf	0.4254
0.7866	0.67	3600	inf	0.4168
0.7413	0.74	4000	inf	0.4168
0.749	0.81	4400	inf	0.4148
0.8165	0.89	4800	inf	0.4241
0.7302	0.96	5200	inf	0.4124
0.7376	1.04	5600	inf	0.4368
0.6833	1.11	6000	inf	0.3953
0.6463	1.19	6400	inf	0.4363
0.7236	1.26	6800	inf	0.4383
0.8837	1.33	7200	inf	0.4811
0.6854	1.41	7600	inf	0.3930
0.6985	1.48	8000	inf	0.3979
0.7139	1.56	8400	inf	0.3977
0.6338	1.63	8800	inf	0.4039
0.7227	1.7	9200	inf	0.3922
0.6843	1.78	9600	inf	0.4111
0.6948	1.85	10000	inf	0.4093
0.6867	1.93	10400	inf	0.3927
0.5753	2.0	10800	inf	0.4080
0.6865	2.07	11200	inf	0.3938
0.6155	2.15	11600	inf	0.3920
0.6743	2.22	12000	inf	0.3977
0.5801	2.3	12400	inf	0.3801
0.8216	2.37	12800	inf	0.3917
0.6199	2.44	13200	inf	0.4052
0.6268	2.52	13600	inf	0.3811
0.6505	2.59	14000	inf	0.3855
0.6578	2.67	14400	inf	0.3933
0.6442	2.74	14800	inf	0.3868
0.5904	2.81	15200	inf	0.3782
0.6249	2.89	15600	inf	0.3788
0.5879	2.96	16000	inf	0.3904
0.4844	3.04	16400	inf	0.3728
0.6309	3.11	16800	inf	0.3687
0.5825	3.19	17200	inf	0.3663
0.7171	3.26	17600	inf	0.3772
0.5471	3.33	18000	inf	0.3718
0.5029	3.41	18400	inf	0.3756
0.5605	3.48	18800	inf	0.3751
0.5582	3.56	19200	inf	0.3728
0.6358	3.63	19600	inf	0.3712
0.4977	3.7	20000	inf	0.3655
0.4828	3.78	20400	inf	0.3671
0.6554	3.85	20800	inf	0.3689
0.561	3.93	21200	inf	0.3702
0.5515	4.0	21600	inf	0.3710

Framework versions

• Transformers 4.33.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.13.1
• Tokenizers 0.12.1