torgo_xlsr_finetune_M01_old

macarious/torgo_xlsr_finetune_M01_old

torgo_xlsr_finetune_M01_old is a automatic speech recognition model from macarious. 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: Nov 19, 2023
Updated: Mar 5, 2024
SHA: d8001a5c

Model card

From the Hugging Face model README

torgo_xlsr_finetune_M01

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: 1.8655
Wer: 0.3060

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.4346	0.89	1000	3.3570	1.0
1.3708	1.79	2000	1.5774	0.7569
0.7783	2.69	3000	1.6546	0.6103
0.5676	3.58	4000	1.3849	0.5216
0.4476	4.48	5000	1.5294	0.5
0.4264	5.37	6000	1.5832	0.4534
0.3434	6.27	7000	1.4397	0.4233
0.3371	7.16	8000	1.4635	0.4129
0.3268	8.06	9000	1.5989	0.3828
0.2623	8.95	10000	1.5145	0.3836
0.2755	9.85	11000	1.6695	0.3569
0.2304	10.74	12000	1.4313	0.3397
0.2052	11.64	13000	1.4242	0.3466
0.199	12.53	14000	1.7287	0.3405
0.2124	13.43	15000	1.4715	0.3086
0.1858	14.32	16000	1.6835	0.3086
0.1667	15.22	17000	1.6080	0.3233
0.1551	16.11	18000	1.6151	0.3293
0.1638	17.01	19000	1.5014	0.3034
0.1584	17.9	20000	1.7036	0.3233
0.1486	18.8	21000	1.6527	0.3207
0.1337	19.7	22000	1.6947	0.3181
0.201	20.59	23000	1.9110	0.3431
0.2058	21.49	24000	1.6260	0.3560
0.1776	22.38	25000	1.8602	0.3483
0.1779	23.28	26000	2.0418	0.3578
0.1401	24.17	27000	2.0262	0.3371
0.1533	25.07	28000	1.7442	0.3069
0.1476	25.96	29000	1.7283	0.3190
0.1414	26.86	30000	1.7655	0.3181
0.1522	27.75	31000	1.6772	0.3103
0.146	28.65	32000	1.4420	0.3
0.1363	29.54	33000	1.5955	0.3276
0.1306	30.44	34000	1.7269	0.3336
0.1241	31.33	35000	1.7725	0.3216
0.1155	32.23	36000	1.8232	0.3086
0.117	33.12	37000	1.8145	0.3052
0.0973	34.02	38000	2.0621	0.3216
0.1181	34.91	39000	1.6758	0.2957
0.1063	35.81	40000	1.6431	0.2983
0.094	36.71	41000	1.7967	0.3069
0.0937	37.6	42000	1.8469	0.3052
0.0931	38.5	43000	1.8364	0.3017
0.0897	39.39	44000	1.8655	0.3060

Framework versions

Transformers 4.26.1
Pytorch 2.1.2
Datasets 2.16.1
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Nov 19, 2023
Updated: Mar 5, 2024