W2V2_Bert_BIG_C_Bemba_50hr_v1

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: 0.6150
• Wer: 0.3709
• Cer: 0.0976

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-06
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.9873	1.0	6423	0.8901	0.6111	0.1723
0.7807	2.0	12846	0.8360	0.5188	0.1525
0.683	3.0	19269	0.6705	0.4842	0.1410
0.6282	4.0	25692	0.6473	0.4762	0.1394
0.594	5.0	32115	0.6369	0.4463	0.1314
0.5645	6.0	38538	0.6244	0.4360	0.1287
0.5322	7.0	44961	0.6186	0.4191	0.1273
0.5045	8.0	51384	0.6334	0.4127	0.1230
0.4767	9.0	57807	0.6017	0.4117	0.1227
0.4505	10.0	64230	0.6142	0.4092	0.1214
0.4247	11.0	70653	0.6155	0.4033	0.1208
0.3974	12.0	77076	0.6161	0.4013	0.1198
0.3714	13.0	83499	0.6415	0.4032	0.1211
0.3437	14.0	89922	0.6691	0.4007	0.1207
0.3175	15.0	96345	0.7251	0.4052	0.1212
0.2921	16.0	102768	0.7279	0.4003	0.1218
0.2681	17.0	109191	0.7837	0.4103	0.1216
0.2455	18.0	115614	0.8336	0.4074	0.1233
0.2242	19.0	122037	0.8544	0.4158	0.1247
0.2044	20.0	128460	0.8591	0.4243	0.1270
0.1857	21.0	134883	0.9652	0.4123	0.1245
0.1676	22.0	141306	1.0143	0.4254	0.1266

Framework versions

• Transformers 4.44.2
• Pytorch 2.2.0+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1