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contemmcm/
dec17dcaf4a4f61c96a22248842aa6fb

Name: dec17dcaf4a4f61c96a22248842aa6fb
Rating: 2.5 (6 reviews)

generated_from_trainer

FacebookAI/xlm-roberta-base

finetune

mit

text-embeddings-inference

endpoints_compatible

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dec17dcaf4a4f61c96a22248842aa6fb

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

Loss: 1.0960
Data Size: 1.0
Epoch Runtime: 1003.2609
Accuracy: 0.3545
F1 Macro: 0.1745
Rouge1: 0.3544
Rouge2: 0.0
Rougel: 0.3545
Rougelsum: 0.3543

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	Rougel	Rougelsum
No log	0	0	1.1034	0	7.6217	0.3545	0.1745	0.3544	0.3545	0.3543
1.1101	1	12271	1.1003	0.0078	16.6881	0.3182	0.1609	0.3184	0.3182	0.3183
1.1062	2	24542	1.0990	0.0156	23.3322	0.3182	0.1609	0.3184	0.3182	0.3183
1.1052	3	36813	1.0981	0.0312	39.0360	0.3273	0.1644	0.3273	0.3275	0.3277
1.1062	4	49084	1.0960	0.0625	70.6372	0.3545	0.1745	0.3544	0.3545	0.3543
1.1028	5	61355	1.0999	0.125	130.9410	0.3182	0.1609	0.3184	0.3182	0.3183
1.1032	6	73626	1.1009	0.25	252.5635	0.3182	0.1609	0.3184	0.3182	0.3183
1.1005	7	85897	1.0960	0.5	499.4349	0.3545	0.1745	0.3544	0.3545	0.3543
1.0998	8.0	98168	1.0952	1.0	993.8908	0.3545	0.1745	0.3544	0.3545	0.3543
1.1006	9.0	110439	1.1014	1.0	990.5599	0.3273	0.1644	0.3273	0.3275	0.3277
1.0982	10.0	122710	1.0980	1.0	985.3294	0.3545	0.1745	0.3544	0.3545	0.3543
1.0988	11.0	134981	1.0992	1.0	993.9275	0.3273	0.1644	0.3273	0.3275	0.3277
1.0988	12.0	147252	1.0960	1.0	1003.2609	0.3545	0.1745	0.3544	0.3545	0.3543

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.3.0
Tokenizers 0.22.1

contemmcm/dec17dcaf4a4f61c96a22248842aa6fb

dec17dcaf4a4f61c96a22248842aa6fb

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

contemmcm/
dec17dcaf4a4f61c96a22248842aa6fb