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dense_est_100m_mult

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

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The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 8
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 9961
training_steps: 99614
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss
5.2265	1.0039	10000	5.1719
4.4313	2.0078	20000	4.4627
4.0517	3.0117	30000	4.2483
3.729	4.0157	40000	4.1565
3.4199	5.0196	50000	4.1415
3.1538	6.0235	60000	4.1736
2.9227	7.0274	70000	4.2458
2.7347	8.0313	80000	4.3328
2.5818	9.0352	90000	4.4188

Safetensors

Model size

0.2B params

Tensor type

F32