daffa-ai-coder-multilang

This model is a fine-tuned version of Salesforce/codet5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.3432
• Rouge1: 0.2895
• Rouge2: 0.1303
• Rougel: 0.2577
• Rougelsum: 0.2894

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 8
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	0.9474	9	5.2760	0.0941	0.0081	0.083	0.0886
7.4467	2.0	19	3.7845	0.1181	0.0207	0.1061	0.1144
4.8513	2.9474	28	3.1986	0.1836	0.0273	0.1569	0.1769
3.9428	4.0	38	2.7966	0.1598	0.0323	0.1541	0.157
3.2332	4.9474	47	2.5789	0.1775	0.0659	0.1704	0.1758
2.9824	6.0	57	2.4343	0.2153	0.0868	0.2064	0.2142
2.7661	6.9474	66	2.3556	0.2678	0.1189	0.2583	0.2706
2.6326	7.5789	72	2.3432	0.2895	0.1303	0.2577	0.2894

Framework versions

• Transformers 4.46.3
• Pytorch 2.11.0+cu128
• Datasets 4.0.0
• Tokenizers 0.20.3