sew-tiny-portuguese-cv8

This model is a fine-tuned version of lgris/sew-tiny-pt on the common_voice dataset. It achieves the following results on the evaluation set:

• Loss: 0.4082
• Wer: 0.3053

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: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• 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: 1000
• training_steps: 40000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	1.93	1000	2.9134	0.9767
2.9224	3.86	2000	2.8405	0.9789
2.9224	5.79	3000	2.8094	0.9800
2.8531	7.72	4000	2.7439	0.9891
2.8531	9.65	5000	2.7057	1.0159
2.7721	11.58	6000	2.7235	1.0709
2.7721	13.51	7000	2.5931	1.1035
2.6566	15.44	8000	2.2171	0.9884
2.6566	17.37	9000	1.2399	0.8081
1.9558	19.31	10000	0.9045	0.6353
1.9558	21.24	11000	0.7705	0.5533
1.4987	23.17	12000	0.7068	0.5165
1.4987	25.1	13000	0.6641	0.4718
1.3811	27.03	14000	0.6043	0.4470
1.3811	28.96	15000	0.5532	0.4268
1.2897	30.89	16000	0.5371	0.4101
1.2897	32.82	17000	0.5924	0.4150
1.225	34.75	18000	0.4949	0.3894
1.225	36.68	19000	0.5591	0.4045
1.193	38.61	20000	0.4927	0.3731
1.193	40.54	21000	0.4922	0.3712
1.1482	42.47	22000	0.4799	0.3662
1.1482	44.4	23000	0.4846	0.3648
1.1201	46.33	24000	0.4770	0.3623
1.1201	48.26	25000	0.4530	0.3426
1.0892	50.19	26000	0.4523	0.3527
1.0892	52.12	27000	0.4573	0.3443
1.0583	54.05	28000	0.4488	0.3353
1.0583	55.98	29000	0.4295	0.3285
1.0319	57.92	30000	0.4321	0.3220
1.0319	59.85	31000	0.4244	0.3236
1.0076	61.78	32000	0.4197	0.3201
1.0076	63.71	33000	0.4230	0.3208
0.9851	65.64	34000	0.4090	0.3127
0.9851	67.57	35000	0.4088	0.3133
0.9695	69.5	36000	0.4123	0.3088
0.9695	71.43	37000	0.4017	0.3090
0.9514	73.36	38000	0.4184	0.3086
0.9514	75.29	39000	0.4075	0.3043
0.944	77.22	40000	0.4082	0.3053

Framework versions

• Transformers 4.16.0.dev0
• Pytorch 1.10.1+cu102
• Datasets 1.17.1.dev0
• Tokenizers 0.11.0