results_german – AI Model by harshvardhanj733 | AlphaNeural AI

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harshvardhanj733/
results_german

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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results_german

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: 1.1187
Accuracy: 0.6630
Precision: 0.6685
Recall: 0.6630
F1: 0.6642

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	181	1.0659	0.4061	0.3156	0.4061	0.3260
No log	2.0	362	1.0165	0.4807	0.5137	0.4807	0.4334
1.0194	3.0	543	0.8416	0.6381	0.6474	0.6381	0.6335
1.0194	4.0	724	0.8182	0.6464	0.6469	0.6464	0.6434
1.0194	5.0	905	0.8988	0.6271	0.6610	0.6271	0.6135
0.7934	6.0	1086	0.8500	0.6657	0.6661	0.6657	0.6654
0.7934	7.0	1267	0.9742	0.6657	0.6722	0.6657	0.6675
0.7934	8.0	1448	1.0340	0.6630	0.6656	0.6630	0.6627
0.6352	9.0	1629	1.0133	0.6575	0.6601	0.6575	0.6586
0.6352	10.0	1810	0.9776	0.6630	0.6689	0.6630	0.6640
0.6352	11.0	1991	1.1097	0.6630	0.6681	0.6630	0.6640
0.5078	12.0	2172	1.1187	0.6630	0.6685	0.6630	0.6642

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1