metadata

license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: emotions_6_classes_small
    results: []

emotions_6_classes_small

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

Loss: 0.9106
Accuracy: 0.7920

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: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 512
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2009	0.99	19	0.6892	0.7891
0.2272	1.97	38	0.7235	0.7817
0.2196	2.96	57	0.7027	0.7809
0.2402	4.0	77	0.7953	0.7592
0.2301	4.99	96	0.7979	0.7699
0.1896	5.97	115	0.7533	0.7838
0.188	6.96	134	0.7483	0.7817
0.1573	8.0	154	0.8200	0.7756
0.1576	8.99	173	0.7623	0.7944
0.1452	9.97	192	0.7460	0.7944
0.1322	10.96	211	0.8031	0.7875
0.1353	12.0	231	0.7864	0.7883
0.1211	12.99	250	0.7934	0.7903
0.1165	13.97	269	0.7734	0.7936
0.0928	14.96	288	0.8743	0.7842
0.095	16.0	308	0.8483	0.7867
0.0824	16.99	327	0.8860	0.7850
0.0896	17.97	346	0.8314	0.7957
0.0874	18.96	365	0.8164	0.7936
0.081	20.0	385	0.8250	0.7993
0.0673	20.99	404	0.9118	0.7879
0.0716	21.97	423	0.8605	0.7912
0.0588	22.96	442	0.8470	0.7985
0.0579	24.0	462	0.8906	0.7920
0.0511	24.99	481	0.8853	0.7969
0.0488	25.97	500	0.8901	0.7973
0.0468	26.96	519	0.9083	0.7895
0.0505	28.0	539	0.9010	0.7903
0.0542	28.99	558	0.8924	0.7944
0.0542	29.61	570	0.9106	0.7920

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3