You can deploy this model and start earning money today!

lazymonster/
adaptation_raw

Name: adaptation_raw
Availability: InStock

generated_from_trainer

lazymonster/20k-combined-raw-scratch

finetune

mit

text-embeddings-inference

endpoints_compatible

Views

No views yet

adaptation_raw

This model is a fine-tuned version of lazymonster/20k-combined-raw-scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.0900
Accuracy: 0.6965
F1 Macro: 0.6952
Composite Score: 0.6952

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Composite Score
No log	1.0	333	0.9958	0.6995	0.6983	0.6983
0.4563	2.0	666	1.0290	0.7104	0.7096	0.7096
0.4563	3.0	999	1.0838	0.6859	0.6840	0.6840
0.4419	4.0	1332	1.0559	0.7006	0.6987	0.6987
0.4108	5.0	1665	1.1011	0.6946	0.6929	0.6929
0.4108	6.0	1998	1.0900	0.6965	0.6952	0.6952

Framework versions

Transformers 4.53.3
Pytorch 2.6.0+cu124
Datasets 4.4.1
Tokenizers 0.21.2

lazymonster/adaptation_raw

adaptation_raw

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lazymonster/
adaptation_raw