Text Generation
Transformers
TensorBoard
Safetensors
llama
Generated from Trainer
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM
tokenizer = AutoTokenizer.from_pretrained("samhitmantrala/badm")
model = AutoModelForMultimodalLM.from_pretrained("samhitmantrala/badm")Quick Links
badm
This model is a fine-tuned version of HuggingFaceTB/SmolLM-360M on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8689
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 1 | 2.0255 |
| No log | 2.0 | 2 | 1.9920 |
| No log | 3.0 | 3 | 1.9635 |
| No log | 4.0 | 4 | 1.9392 |
| No log | 5.0 | 5 | 1.9187 |
| No log | 6.0 | 6 | 1.9019 |
| No log | 7.0 | 7 | 1.8886 |
| No log | 8.0 | 8 | 1.8787 |
| No log | 9.0 | 9 | 1.8722 |
| No log | 10.0 | 10 | 1.8689 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for samhitmantrala/badm
Base model
HuggingFaceTB/SmolLM-360M
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="samhitmantrala/badm")