README.md

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: 0.1603
• Wer: 0.1145

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
1.0491	0.47	600	0.3405	0.4429
0.1667	0.95	1200	0.2590	0.3481
0.1213	1.42	1800	0.2217	0.3055
0.1021	1.9	2400	0.1943	0.2839
0.0822	2.37	3000	0.1861	0.2341
0.0739	2.85	3600	0.1681	0.2302
0.062	3.32	4200	0.1669	0.2065
0.0543	3.8	4800	0.1727	0.2115
0.0434	4.27	5400	0.1581	0.1826
0.0378	4.74	6000	0.1544	0.1963
0.0349	5.22	6600	0.1415	0.1680
0.0266	5.69	7200	0.1504	0.1607
0.0226	6.17	7800	0.1471	0.1485
0.0186	6.64	8400	0.1435	0.1456
0.0163	7.12	9000	0.1415	0.1331
0.0117	7.59	9600	0.1413	0.1309
0.0119	8.07	10200	0.1618	0.1214
0.0076	8.54	10800	0.1545	0.1194
0.0068	9.02	11400	0.1553	0.1204
0.0038	9.49	12000	0.1584	0.1177
0.0036	9.96	12600	0.1603	0.1145

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.1+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1