Datasetpublic

gonzalobenegas/gpn-animal-promoter-early-checkpoints

checkpoints This model is a fine-tuned version of on the dataset dataset. It achieves the following results on the evaluation set: Loss: 1.2163 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:… See the full description on the dataset page: https://huggingface.co/datasets/gonzalobenegas/gpn-animal-promoter-early-checkpoints.

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checkpoints

This model is a fine-tuned version of [](https://huggingface.co/) on the dataset dataset. It achieves the following results on the evaluation set:

—Loss: 1.2163

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: 0.001
—trainbatchsize: 128
—evalbatchsize: 128
—seed: 42
—distributed_type: multi-GPU
—num_devices: 8
—gradientaccumulationsteps: 2
—totaltrainbatch_size: 2048
—totalevalbatch_size: 1024
—optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
—lrschedulertype: constantwithwarmup
—lrschedulerwarmup_steps: 1000
—training_steps: 10000

Training results

Training Loss	Epoch	Step	Validation Loss
1.2665	0.1	1000	1.2514
1.2196	0.2	2000	1.2411
1.2079	0.3	3000	1.2353
1.2018	0.4	4000	1.2307
1.1977	1.0592	5000	1.2273
1.1949	1.1592	6000	1.2242
1.1925	1.2592	7000	1.2245
1.1906	1.3592	8000	1.2222
1.1883	2.0184	9000	1.2193
1.1868	2.1184	10000	1.2175

Framework versions

—Transformers 4.57.1
—Pytorch 2.9.1+cu128
—Datasets 4.4.1
—Tokenizers 0.22.1