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MateiCv/
results

Name: results
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generated_from_trainer

distilbert/distilbert-base-multilingual-cased

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results

This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5702
Accuracy: 0.7894
Precision: 0.7913
Recall: 0.7040
F1: 0.7144
Hamming Loss: 0.2106

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: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Hamming Loss
1.435	1.0	1744	1.2662	0.5627	0.6403	0.4392	0.4707	0.4373
1.19	2.0	3488	1.0175	0.6358	0.6749	0.5311	0.5571	0.3642
0.9496	3.0	5232	0.8298	0.6934	0.7166	0.5916	0.6132	0.3066
0.8226	4.0	6976	0.7224	0.7306	0.7447	0.6371	0.6561	0.2694
0.7113	5.0	8720	0.6609	0.7514	0.7628	0.6583	0.6742	0.2486
0.6497	6.0	10464	0.6153	0.7724	0.7717	0.6904	0.6980	0.2276
0.5997	7.0	12208	0.5822	0.7863	0.7945	0.6967	0.7105	0.2137
0.571	8.0	13952	0.5702	0.7894	0.7913	0.7040	0.7144	0.2106

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu118
Tokenizers 0.13.3

MateiCv/results

results

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MateiCv/
results