marklicata
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M365_demo

Text Classification

Generated from Trainer

text-embeddings-inference

Model card Files Files and versions

M365_demo

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

Loss: 1.3005

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss
2.4639	1.0	520	1.8732
1.6752	2.0	1040	1.4187
1.3741	3.0	1560	1.3005

Framework versions

Transformers 4.44.2
Pytorch 2.3.1+cpu
Datasets 2.20.0
Tokenizers 0.19.1

Downloads last month: 4

Safetensors

Model size

67M params

Tensor type

F32

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