mt5-small-task2-dataset3

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3113
• Accuracy: 0.704

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: 5.6e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3153	1.0	250	0.7513	0.526
0.8878	2.0	500	0.5870	0.576
0.7191	3.0	750	0.5021	0.578
0.5842	4.0	1000	0.4596	0.612
0.5085	5.0	1250	0.4158	0.62
0.4515	6.0	1500	0.3865	0.618
0.4086	7.0	1750	0.3755	0.648
0.3811	8.0	2000	0.3505	0.662
0.3449	9.0	2250	0.3366	0.678
0.3294	10.0	2500	0.3280	0.674
0.3146	11.0	2750	0.3201	0.702
0.305	12.0	3000	0.3146	0.69
0.2972	13.0	3250	0.3130	0.702
0.2819	14.0	3500	0.3106	0.696
0.2828	15.0	3750	0.3113	0.704

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.15.0
• Tokenizers 0.15.0