t5-small-vanilla-mtop

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: 0.1581
• Exact Match: 0.6331

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: 0.001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 512
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Exact Match
1.5981	6.65	200	0.1598	0.4940
0.1335	13.33	400	0.1155	0.5884
0.074	19.98	600	0.1046	0.6094
0.0497	26.65	800	0.1065	0.6139
0.0363	33.33	1000	0.1134	0.6255
0.0278	39.98	1200	0.1177	0.6313
0.022	46.65	1400	0.1264	0.6255
0.0183	53.33	1600	0.1260	0.6304
0.0151	59.98	1800	0.1312	0.6300
0.0124	66.65	2000	0.1421	0.6277
0.0111	73.33	2200	0.1405	0.6277
0.0092	79.98	2400	0.1466	0.6331
0.008	86.65	2600	0.1522	0.6340
0.007	93.33	2800	0.1590	0.6295
0.0064	99.98	3000	0.1581	0.6331

Framework versions

• Transformers 4.24.0
• Pytorch 1.13.0+cu117
• Datasets 2.7.0
• Tokenizers 0.13.2