t5-base-pointer-cstop_artificial

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

• Loss: 0.0776
• Exact Match: 0.7746

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
1.7482	28.5	200	0.2505	0.1020
0.1366	57.13	400	0.0776	0.3238
0.0275	85.63	600	0.0881	0.3381
0.0114	114.25	800	0.0990	0.3399
0.0064	142.75	1000	0.1120	0.3417
0.0045	171.38	1200	0.1081	0.3435
0.0036	199.88	1400	0.1230	0.3435
0.0025	228.5	1600	0.1211	0.3399
0.002	257.13	1800	0.1367	0.3399
0.0016	285.63	2000	0.1324	0.3435
0.0013	314.25	2200	0.1340	0.3470
0.001	342.75	2400	0.1374	0.3435
0.0009	371.38	2600	0.1384	0.3417
0.0007	399.88	2800	0.1422	0.3435
0.0006	428.5	3000	0.1452	0.3417

Framework versions

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