t5-base-pointer-mtop

This model is a fine-tuned version of google/mt5-base on the mtop dataset. It achieves the following results on the evaluation set:

• Loss: 0.1131
• Exact Match: 0.7199

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 64
• 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
1.7749	6.65	200	0.5892	0.0031
0.6021	13.33	400	0.5160	0.0139
0.6044	19.98	600	0.4080	0.0532
0.3302	26.65	800	0.1865	0.3620
0.1483	33.33	1000	0.1267	0.5105
0.0768	39.98	1200	0.1131	0.5298
0.0525	46.65	1400	0.1219	0.5414
0.0801	53.33	1600	0.1186	0.5275
0.0331	59.98	1800	0.1306	0.5423
0.0254	66.65	2000	0.1396	0.5396
0.0168	73.33	2200	0.1560	0.5436
0.0129	79.98	2400	0.1659	0.5494
0.0105	86.65	2600	0.1699	0.5423
0.0088	93.33	2800	0.1742	0.5472
0.0077	99.98	3000	0.1775	0.5468

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu117
• Datasets 2.7.1
• Tokenizers 0.13.2