metadata

license: mit
base_model: facebook/w2v-bert-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: w2v-bert-2.0-malayalam_mixeddataset_thre
    results: []

w2v-bert-2.0-malayalam_mixeddataset_thre

This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1604
Wer: 0.1244

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: 5e-05
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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.1974	0.47	600	0.3732	0.4971
0.1677	0.95	1200	0.2552	0.3411
0.1229	1.42	1800	0.2184	0.3123
0.1041	1.9	2400	0.2044	0.2921
0.0825	2.37	3000	0.2150	0.2667
0.0756	2.85	3600	0.1882	0.2361
0.0627	3.32	4200	0.1735	0.2493
0.0557	3.8	4800	0.1653	0.2117
0.0454	4.27	5400	0.1669	0.1891
0.0394	4.74	6000	0.1610	0.1903
0.0363	5.22	6600	0.1654	0.1699
0.0278	5.69	7200	0.1465	0.1640
0.025	6.17	7800	0.1503	0.1617
0.0198	6.64	8400	0.1429	0.1466
0.0174	7.12	9000	0.1440	0.1453
0.013	7.59	9600	0.1496	0.1433
0.0125	8.07	10200	0.1465	0.1274
0.0076	8.54	10800	0.1479	0.1349
0.0076	9.02	11400	0.1521	0.1229
0.0041	9.49	12000	0.1600	0.1291
0.0038	9.96	12600	0.1604	0.1244

Framework versions

Transformers 4.39.3
Pytorch 2.1.1+cu121
Datasets 2.16.1
Tokenizers 0.15.1