Scottie201/custom_model_trained

fine-tuned-custom-model

This model is a fine-tuned version of HuggingFaceTB/SmolLM2-1.7B-Instruct on the Scottie201 dataset.
It achieves the following results on the evaluation set:

• Loss: 2.3012
• Evaluation Runtime: 125.50 seconds
• Evaluation Samples per Second: 0.096
• Evaluation Steps per Second: 0.048

Model description

This is a fine-tuned version of the HuggingFaceTB/SmolLM2-1.7B-Instruct model, trained to handle custom tasks related to text generation. The model can handle a wide range of text completion, summarization, and question-answering tasks.

Intended uses & limitations

The model can be used for tasks like:

• Text generation
• Question answering
• Summarization
• General text-based tasks

Limitations:

• May not work well for domain-specific tasks that were not part of the training data.
• Performance on unseen data may vary depending on the domain of the query.

Training and evaluation data

The model was trained and evaluated on the Scottie201 dataset, which includes various text-based tasks. The evaluation was carried out after 2 epochs of training.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
2.4066	1.0	25	2.3138
2.3976	2.0	50	2.3012

Evaluation results

Evaluation Metric	Value
Loss	2.3012
Runtime	125.50 sec
Samples per Second	0.096
Steps per Second	0.048

Framework versions

• Transformers: 4.48.3
• PyTorch: 2.6.0+cu124
• Datasets: 3.2.0
• Tokenizers: 0.21.0

---

This model card now includes detailed information about the evaluation procedure, training results, and evaluation results such as loss, runtime, and throughput. The evaluation metric table provides clarity on how the model performed during evaluation.

Let me know if you'd like any more adjustments or additional details!