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web2savar/
w2v-fine-tune-test-no-ws2

Name: w2v-fine-tune-test-no-ws2
Availability: InStock

transformers

safetensors

wav2vec2-bert

automatic-speech-recognition

generated_from_trainer

common_voice_16_0

ylacombe/w2v-bert-2.0

finetune

model-index

endpoints_compatible

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w2v-fine-tune-test-no-ws2

This model is a fine-tuned version of ylacombe/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1513
Wer: 0.1109

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: 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: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.192	0.22	300	0.2797	0.2985
0.2226	0.44	600	0.2989	0.3491
0.1941	0.66	900	0.2558	0.2451
0.1659	0.88	1200	0.2320	0.2289
0.1332	1.1	1500	0.2063	0.1971
0.1129	1.31	1800	0.1873	0.2029
0.1044	1.53	2100	0.1765	0.1856
0.1026	1.75	2400	0.1719	0.1752
0.0982	1.97	2700	0.1927	0.2023
0.0769	2.19	3000	0.1776	0.1671
0.0715	2.41	3300	0.1626	0.1634
0.0695	2.63	3600	0.1666	0.1654
0.0612	2.85	3900	0.1760	0.1609
0.0614	3.07	4200	0.1645	0.1593
0.0476	3.29	4500	0.1685	0.1593
0.048	3.51	4800	0.1790	0.1583
0.0489	3.73	5100	0.1578	0.1535
0.0456	3.94	5400	0.1610	0.1617
0.041	4.16	5700	0.1559	0.1439
0.0367	4.38	6000	0.1536	0.1436
0.0321	4.6	6300	0.1591	0.1449
0.0349	4.82	6600	0.1616	0.1419
0.0308	5.04	6900	0.1501	0.1401
0.0233	5.26	7200	0.1588	0.1394
0.0253	5.48	7500	0.1633	0.1356
0.0254	5.7	7800	0.1522	0.1339
0.0245	5.92	8100	0.1598	0.1371
0.0189	6.14	8400	0.1497	0.1324
0.0174	6.36	8700	0.1487	0.1270
0.0178	6.57	9000	0.1397	0.1286
0.0173	6.79	9300	0.1495	0.1281
0.0178	7.01	9600	0.1462	0.1222
0.0124	7.23	9900	0.1516	0.1225
0.0121	7.45	10200	0.1554	0.1190
0.0128	7.67	10500	0.1453	0.1228
0.0113	7.89	10800	0.1468	0.1178
0.0086	8.11	11100	0.1556	0.1186
0.0085	8.33	11400	0.1507	0.1154
0.0073	8.55	11700	0.1494	0.1169
0.0079	8.77	12000	0.1507	0.1152
0.0089	8.98	12300	0.1456	0.1137
0.0062	9.2	12600	0.1518	0.1127
0.005	9.42	12900	0.1534	0.1115
0.005	9.64	13200	0.1514	0.1110
0.0048	9.86	13500	0.1513	0.1109

Framework versions

Transformers 4.37.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.1

web2savar/w2v-fine-tune-test-no-ws2

w2v-fine-tune-test-no-ws2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

web2savar/
w2v-fine-tune-test-no-ws2