imja

kadriu/imja

imja is a automatic speech recognition model from kadriu. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Oct 17, 2023
Updated: Oct 17, 2023
SHA: cc457f31

Model card

From the Hugging Face model README

wav2vec2-large-xlsr-53-Total2e-4_4

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2474
Wer: 0.1951

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: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.5015	0.1	200	2.9261	0.9707
2.9197	0.2	400	2.7757	0.9707
1.7594	0.3	600	0.6117	0.5746
1.0908	0.4	800	0.4673	0.4530
0.9441	0.5	1000	0.4142	0.4010
0.8688	0.6	1200	0.3909	0.3675
0.849	0.7	1400	0.3649	0.3360
0.8223	0.8	1600	0.3532	0.3334
0.821	0.9	1800	0.3513	0.3185
0.7839	1.0	2000	0.3373	0.3039
0.714	1.1	2200	0.3210	0.2922
0.7129	1.2	2400	0.3216	0.2860
0.7076	1.3	2600	0.3279	0.2843
0.73	1.4	2800	0.3111	0.2662
0.7256	1.5	3000	0.3032	0.2625
0.72	1.6	3200	0.3066	0.2571
0.6754	1.7	3400	0.2999	0.2581
0.6859	1.8	3600	0.2935	0.2562
0.6966	1.9	3800	0.2858	0.2469
0.6791	2.0	4000	0.2857	0.2393
0.6412	2.1	4200	0.2815	0.2392
0.6356	2.2	4400	0.2836	0.2343
0.6048	2.3	4600	0.2824	0.2422
0.6473	2.4	4800	0.2805	0.2316
0.659	2.5	5000	0.2775	0.2262
0.6412	2.6	5200	0.2729	0.2249
0.6167	2.7	5400	0.2719	0.2227
0.6226	2.8	5600	0.2661	0.2193
0.6168	2.9	5800	0.2615	0.2172
0.6145	3.0	6000	0.2608	0.2148
0.593	3.1	6200	0.2643	0.2123
0.5919	3.2	6400	0.2617	0.2131
0.6115	3.3	6600	0.2589	0.2114
0.5859	3.4	6800	0.2591	0.2100
0.5919	3.5	7000	0.2564	0.2103
0.5873	3.6	7200	0.2572	0.2074
0.561	3.7	7400	0.2561	0.2056
0.5808	3.8	7600	0.2538	0.2062
0.5701	3.9	7800	0.2517	0.2029
0.5722	4.0	8000	0.2523	0.2007
0.5508	4.1	8200	0.2570	0.2023
0.5591	4.2	8400	0.2502	0.2029
0.5697	4.3	8600	0.2478	0.1991
0.5689	4.4	8800	0.2492	0.2021
0.5345	4.5	9000	0.2498	0.2005
0.5726	4.6	9200	0.2492	0.1983
0.5382	4.7	9400	0.2487	0.1974
0.5614	4.8	9600	0.2481	0.1957
0.5568	4.9	9800	0.2477	0.1955
0.5631	5.0	10000	0.2474	0.1951

Framework versions

Transformers 4.15.0
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.10.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Oct 17, 2023
Updated: Oct 17, 2023