wav2vec2-base-finetuned-ravdess

Wiam/wav2vec2-base-finetuned-ravdess

wav2vec2-base-finetuned-ravdess is a audio classification model from Wiam. Use it for the audio classification task on the model card, and read the license before you ship it in a product. 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. --

Downloads · 30 days

2% of all-time downloads

All-time downloads

2.7K

Public

Repo size

40.1 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin378 MB · 100%

At a glance

Task: Audio Classification
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Aug 16, 2023
Updated: Aug 17, 2023
SHA: 78b9344c

Base models

facebook/wav2vec2-base

Model card

From the Hugging Face model README

wav2vec2-base-finetuned-ravdess

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8783
Accuracy: 0.7535

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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	9	2.0739	0.1562
2.0781	2.0	18	2.0611	0.1181
2.0668	3.0	27	2.0308	0.2535
2.0429	4.0	36	1.9606	0.2604
1.974	5.0	45	1.8449	0.2847
1.8594	6.0	54	1.7678	0.2917
1.7675	7.0	63	1.7700	0.2708
1.6932	8.0	72	1.6049	0.3889
1.5656	9.0	81	1.5510	0.4444
1.4658	10.0	90	1.4535	0.4583
1.4658	11.0	99	1.4101	0.4514
1.3843	12.0	108	1.3687	0.5
1.3085	13.0	117	1.3333	0.5035
1.2264	14.0	126	1.3208	0.5208
1.1349	15.0	135	1.3048	0.5312
1.0861	16.0	144	1.2428	0.5799
0.9836	17.0	153	1.1886	0.5799
0.9273	18.0	162	1.1574	0.6146
0.8686	19.0	171	1.1356	0.6111
0.814	20.0	180	1.1261	0.6285
0.814	21.0	189	1.0796	0.6007
0.7279	22.0	198	1.0277	0.6493
0.6845	23.0	207	1.0408	0.6840
0.6283	24.0	216	0.9708	0.7153
0.5835	25.0	225	0.9926	0.6875
0.5445	26.0	234	1.0126	0.6840
0.497	27.0	243	0.9502	0.6979
0.4508	28.0	252	0.9432	0.7118
0.4331	29.0	261	0.9246	0.7014
0.4023	30.0	270	0.9649	0.6875
0.4023	31.0	279	0.9114	0.7049
0.3924	32.0	288	0.9460	0.7118
0.3797	33.0	297	0.9605	0.7118
0.3494	34.0	306	0.8505	0.7396
0.3195	35.0	315	0.8830	0.7188
0.3148	36.0	324	0.9352	0.7014
0.2856	37.0	333	0.8551	0.7292
0.2831	38.0	342	0.8505	0.7326
0.2718	39.0	351	0.8800	0.7396
0.2624	40.0	360	0.8991	0.7153
0.2624	41.0	369	0.8724	0.7465
0.2612	42.0	378	0.9138	0.7049
0.2511	43.0	387	0.8914	0.7257
0.2324	44.0	396	0.8783	0.7535
0.2228	45.0	405	0.9215	0.7188
0.2244	46.0	414	0.8904	0.7431
0.2192	47.0	423	0.9142	0.7326
0.217	48.0	432	0.8891	0.7361
0.2146	49.0	441	0.9009	0.7326
0.215	50.0	450	0.8994	0.7361

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

Task: Audio Classification
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Aug 16, 2023
Updated: Aug 17, 2023