sentiment_analysis_model

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

• Loss: 1.3312
• Accuracy: 0.7107
• Precision: 0.1777
• F1: 0.2077

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: 1e-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: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	F1
No log	1.0	4	1.3312	0.7107	0.1777	0.2077
No log	2.0	8	1.2993	0.7107	0.1777	0.2077
1.3368	3.0	12	1.2879	0.7107	0.1777	0.2077

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu118
• Datasets 2.14.5
• Tokenizers 0.15.2