DACTYL Finetuned SLMs
Collection
These are models that were continued pretrained on a domain-specific corpus.
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20 items
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Updated
fine-tuned-Llama-3.2-1B-Instruct-apollo-mini-tweets-validation
This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct on the None dataset.
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use apollo_adamw with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=proj=random,rank=1,scale=128.0,scale_type=tensor,update_proj_gap=200
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 45
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 105 | 3.7892 |
Framework versions
- Transformers 4.52.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for ShantanuT01/fine-tuned-Llama-3.2-1B-Instruct-apollo-mini-tweets-validation
Base model
meta-llama/Llama-3.2-1B-Instruct