xlm-roberta-profane-final – AI Model by SiddharthaM | AlphaNeural AI

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SiddharthaM/
xlm-roberta-profane-final

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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xlm-roberta-profane-final

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3272
Accuracy: 0.9087
Precision: 0.8411
Recall: 0.8441
F1: 0.8426

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: 1e-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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	296	0.2705	0.9030	0.8368	0.8192	0.8276
0.3171	2.0	592	0.2174	0.9192	0.8847	0.8204	0.8476
0.3171	3.0	888	0.2250	0.9202	0.8658	0.8531	0.8593
0.2162	4.0	1184	0.2329	0.9106	0.8422	0.8538	0.8478
0.2162	5.0	1480	0.2260	0.9183	0.8584	0.8584	0.8584
0.1766	6.0	1776	0.2638	0.9116	0.8409	0.8651	0.8522
0.146	7.0	2072	0.3088	0.9125	0.8494	0.8464	0.8478
0.146	8.0	2368	0.2873	0.9154	0.8568	0.8459	0.8512
0.1166	9.0	2664	0.3227	0.9144	0.8518	0.8518	0.8518
0.1166	10.0	2960	0.3272	0.9087	0.8411	0.8441	0.8426

Framework versions

Transformers 4.24.0.dev0
Pytorch 1.11.0+cu102
Datasets 2.6.1
Tokenizers 0.13.1