runyankore_speech_to_intent_wav2vec_xlsr_4ctc

KasuleTrevor/runyankore_speech_to_intent_wav2vec_xlsr_4ctc

runyankore_speech_to_intent_wav2vec_xlsr_4ctc is a text classification model from KasuleTrevor. Use it when you need a label for a piece of text. It is set up for transformers.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: wav2vec2
Access: Public
Created: Aug 20, 2024
Updated: Aug 20, 2024
SHA: d8a4a925

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Base models

KasuleTrevor/wav2vec2-xls-r-300m-nyn_filtered-yogera-v3

Model card

From the Hugging Face model README

runyankore_speech_to_intent_wav2vec_xlsr_4ctc

This model is a fine-tuned version of KasuleTrevor/wav2vec2-xls-r-300m-nyn_filtered-yogera-v3 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1380
Accuracy: 0.9836
Precision: 0.9844
Recall: 0.9836
F1: 0.9837

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: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 500
num_epochs: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	88	2.8252	0.2648	0.1611	0.2648	0.1636
2.9339	2.0	176	1.2106	0.7984	0.7228	0.7984	0.7364
1.8912	3.0	264	0.1829	0.9756	0.9771	0.9756	0.9757
0.3454	4.0	352	0.1177	0.9776	0.9796	0.9776	0.9778
0.1317	5.0	440	0.1024	0.9796	0.9808	0.9796	0.9797
0.1059	6.0	528	0.0994	0.9796	0.9807	0.9796	0.9796
0.0926	7.0	616	0.0834	0.9776	0.9784	0.9776	0.9777
0.0775	8.0	704	0.1048	0.9776	0.9783	0.9776	0.9777
0.0775	9.0	792	0.0947	0.9756	0.9764	0.9756	0.9756
0.0522	10.0	880	0.1098	0.9796	0.9811	0.9796	0.9798
0.0487	11.0	968	0.1159	0.9796	0.9808	0.9796	0.9797
0.035	12.0	1056	0.1116	0.9817	0.9831	0.9817	0.9818
0.0335	13.0	1144	0.1134	0.9796	0.9804	0.9796	0.9797
0.0298	14.0	1232	0.1239	0.9776	0.9790	0.9776	0.9777
0.0248	15.0	1320	0.1186	0.9817	0.9823	0.9817	0.9817
0.0217	16.0	1408	0.1217	0.9776	0.9782	0.9776	0.9776
0.0217	17.0	1496	0.1101	0.9817	0.9823	0.9817	0.9817
0.0293	18.0	1584	0.1174	0.9837	0.9846	0.9837	0.9838
0.0222	19.0	1672	0.1326	0.9796	0.9802	0.9796	0.9797
0.0267	20.0	1760	0.1142	0.9837	0.9850	0.9837	0.9839
0.0217	21.0	1848	0.1166	0.9817	0.9824	0.9817	0.9817
0.0174	22.0	1936	0.1165	0.9796	0.9801	0.9796	0.9796
0.0198	23.0	2024	0.1274	0.9796	0.9806	0.9796	0.9797
0.0142	24.0	2112	0.1351	0.9796	0.9809	0.9796	0.9798
0.0204	25.0	2200	0.1377	0.9776	0.9782	0.9776	0.9776
0.0204	26.0	2288	0.1239	0.9776	0.9783	0.9776	0.9775
0.0173	27.0	2376	0.1565	0.9776	0.9794	0.9776	0.9778
0.0204	28.0	2464	0.1233	0.9817	0.9825	0.9817	0.9818

Framework versions

Transformers 4.44.1
Pytorch 2.1.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: wav2vec2
Created: Aug 20, 2024
Updated: Aug 20, 2024