xlmr-large-AmDi-synset-classifier – AI Model by kugler | AlphaNeural AI

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kugler/
xlmr-large-AmDi-synset-classifier

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-large

autotrain_compatible

endpoints_compatible

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xlmr_synset_classifier

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5821
Accuracy: 0.8300
F1: 0.8189
Precision: 0.8299
Recall: 0.8300
F1 Macro: 0.6291
Precision Macro: 0.6111
Recall Macro: 0.6637
F1 Micro: 0.8300
Precision Micro: 0.8300
Recall Micro: 0.8300

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: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	F1 Macro	Precision Macro	Recall Macro	F1 Micro	Precision Micro	Recall Micro
3.6302	0.6221	100	2.3997	0.4612	0.3541	0.3218	0.4612	0.1136	0.1245	0.1308	0.4612	0.4612	0.4612
1.6212	1.2442	200	0.9750	0.7479	0.7052	0.7046	0.7479	0.4218	0.4214	0.4650	0.7479	0.7479	0.7479
0.9307	1.8663	300	0.7650	0.7936	0.7685	0.7863	0.7936	0.5217	0.5204	0.5619	0.7936	0.7936	0.7936
0.6977	2.4883	400	0.6956	0.8089	0.7935	0.8090	0.8089	0.5696	0.5599	0.6015	0.8089	0.8089	0.8089
0.6152	3.1104	500	0.6451	0.8188	0.8051	0.8224	0.8188	0.6021	0.5949	0.6321	0.8188	0.8188	0.8188
0.5171	3.7325	600	0.5960	0.8331	0.8209	0.8322	0.8331	0.6287	0.6304	0.6524	0.8331	0.8331	0.8331
0.4772	4.3546	700	0.5903	0.8286	0.8178	0.8291	0.8286	0.6305	0.6244	0.6587	0.8286	0.8286	0.8286
0.437	4.9767	800	0.5821	0.8300	0.8189	0.8299	0.8300	0.6291	0.6111	0.6637	0.8300	0.8300	0.8300

Framework versions

Transformers 4.45.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.20.3