xlm-v-base-finetuned-xglue-xnli – AI Model by mrm8488 | AlphaNeural AI

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mrm8488/
xlm-v-base-finetuned-xglue-xnli

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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XLM-V (base) fine-tuned on XNLI

This model is a fine-tuned version of XLM-V (base) on the XNLI (XGLUE) dataset. It achieves the following results on the evaluation set:

Loss: 0.6511
Accuracy: 0.7403

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0994	0.08	1000	1.0966	0.3697
1.0221	0.16	2000	1.0765	0.4560
0.8437	0.24	3000	0.8472	0.6179
0.6997	0.33	4000	0.7650	0.6804
0.6304	0.41	5000	0.7227	0.7007
0.5972	0.49	6000	0.7430	0.6977
0.5886	0.57	7000	0.7365	0.7066
0.5585	0.65	8000	0.6819	0.7223
0.5464	0.73	9000	0.7222	0.7046
0.5289	0.81	10000	0.7290	0.7054
0.5298	0.9	11000	0.6824	0.7221
0.5241	0.98	12000	0.6650	0.7268
0.4806	1.06	13000	0.6861	0.7308
0.4715	1.14	14000	0.6619	0.7304
0.4645	1.22	15000	0.6656	0.7284
0.4443	1.3	16000	0.7026	0.7270
0.4582	1.39	17000	0.7055	0.7225
0.4456	1.47	18000	0.6592	0.7361
0.44	1.55	19000	0.6816	0.7329
0.4419	1.63	20000	0.6772	0.7357
0.4403	1.71	21000	0.6745	0.7319
0.4348	1.79	22000	0.6678	0.7338
0.4355	1.87	23000	0.6614	0.7365
0.4295	1.96	24000	0.6511	0.7403

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2