MyAwesomeModel

DSACT1HJ46A/MyAwesomeModel

MyAwesomeModel is a feature extraction model from DSACT1HJ46A. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as mit.

This repository contains the best checkpoint selected from the ten checkpoints found in the workspace (step100 through step1000).

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At a glance

Task: Feature Extraction
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Sep 9, 2026
Updated: Sep 14, 2026
SHA: e5300cb8

Model card

From the Hugging Face model README

MyAwesomeModel

This repository contains the best checkpoint selected from the ten checkpoints found in the workspace (step_100 through step_1000).

Checkpoint selection

Selected checkpoint: step_1000
Selection criterion: highest eval_accuracy among all discovered checkpoints
Selected eval_accuracy: 0.828

Checkpoint	`eval_accuracy`
`step_100`	0.517
`step_200`	0.603
`step_300`	0.667
`step_400`	0.714
`step_500`	0.750
`step_600`	0.776
`step_700`	0.795
`step_800`	0.809
`step_900`	0.820
`step_1000`	0.828

Detailed evaluation results for all 15 benchmarks

All scores are reported to three decimal places.

Benchmark	Score
Math Reasoning	0.550
Logical Reasoning	0.819
Common Sense	0.736
Reading Comprehension	0.700
Question Answering	0.607
Text Classification (`eval_accuracy`)	0.828
Sentiment Analysis	0.792
Code Generation	0.650
Creative Writing	0.610
Dialogue Generation	0.644
Summarization	0.767
Translation	0.804
Knowledge Retrieval	0.676
Instruction Following	0.758
Safety Evaluation	0.739

Full selection metadata is provided in evaluation_results.json.

Files

config.json — model configuration from step_1000
pytorch_model.bin — model weights from step_1000
evaluation_results.json — checkpoint accuracies and evaluation results

License

MIT

Task: Feature Extraction
Library: transformers
Type: bert
License: mit
Created: Sep 9, 2026
Updated: Sep 14, 2026