da16708d1e95274fac72e230943eeaa6

This model is a fine-tuned version of FacebookAI/xlm-roberta-large-finetuned-conll03-english on the nyu-mll/glue [cola] dataset. It achieves the following results on the evaluation set:

• Loss: 0.6258
• Data Size: 1.0
• Epoch Runtime: 45.9671
• Accuracy: 0.6885
• F1 Macro: 0.4078
• Rouge1: 0.6895
• Rouge2: 0.0
• Rougel: 0.6885
• Rougelsum: 0.6885

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
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Accuracy	F1 Macro	Rouge1	Rouge2	Rougel	Rougelsum
No log	0	0	0.6667	0	2.0834	0.6660	0.4747	0.6670	0.0	0.6660	0.6660
No log	1	267	0.6588	0.0078	3.3472	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	2	534	0.6263	0.0156	3.5510	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	3	801	0.6221	0.0312	4.9079	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	4	1068	0.6600	0.0625	6.7522	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.0391	5	1335	0.6218	0.125	9.9759	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6139	6	1602	0.6218	0.25	15.4786	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6205	7	1869	0.6759	0.5	26.6416	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6066	8.0	2136	0.6209	1.0	47.3189	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6126	9.0	2403	0.6540	1.0	45.7860	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6155	10.0	2670	0.6205	1.0	45.1242	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6228	11.0	2937	0.6260	1.0	45.8124	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6256	12.0	3204	0.6257	1.0	45.6364	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6174	13.0	3471	0.6212	1.0	46.6147	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6301	14.0	3738	0.6258	1.0	45.9671	0.6885	0.4078	0.6895	0.0	0.6885	0.6885

Framework versions

• Transformers 4.57.0
• Pytorch 2.8.0+cu128
• Datasets 4.3.0
• Tokenizers 0.22.1