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# lmind_nq_train600_eval300_v1_qa_tyzhu_lmind_nq_train600_eval300_v1_docidx_gpt2-xl

This model is a fine-tuned version of [tyzhu/lmind_nq_train600_eval300_v1_docidx_gpt2-xl](https://huggingface.co/tyzhu/lmind_nq_train600_eval300_v1_docidx_gpt2-xl) on the tyzhu/lmind_nq_train600_eval300_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9583
- Accuracy: 0.4439

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.9871        | 0.5   | 19   | 2.6569          | 0.4256   |
| 2.5621        | 1.0   | 38   | 2.3482          | 0.4481   |
| 1.7685        | 1.5   | 57   | 2.3878          | 0.4511   |
| 1.7329        | 2.0   | 76   | 2.3360          | 0.4540   |
| 0.9683        | 2.5   | 95   | 2.4967          | 0.4458   |
| 1.0497        | 3.0   | 114  | 2.5784          | 0.4484   |
| 0.6879        | 3.5   | 133  | 2.6868          | 0.4451   |
| 0.745         | 4.0   | 152  | 2.6853          | 0.4446   |
| 0.5647        | 4.5   | 171  | 2.8144          | 0.4426   |
| 0.6076        | 5.0   | 190  | 2.7741          | 0.4431   |
| 0.5071        | 5.5   | 209  | 2.7733          | 0.4385   |
| 0.5671        | 6.0   | 228  | 2.8662          | 0.4411   |
| 0.5215        | 6.5   | 247  | 2.8325          | 0.4360   |
| 0.4928        | 7.0   | 266  | 2.8655          | 0.4361   |
| 0.4663        | 7.5   | 285  | 2.8576          | 0.4340   |
| 0.4959        | 8.0   | 304  | 2.9231          | 0.4416   |
| 0.4219        | 8.5   | 323  | 2.9107          | 0.4431   |
| 0.4886        | 9.0   | 342  | 2.8667          | 0.4433   |
| 0.4103        | 9.5   | 361  | 2.9732          | 0.4392   |
| 0.4672        | 10.0  | 380  | 2.9583          | 0.4439   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/lmind_nq_train600_eval300_v1_qa"], "metrics": ["accuracy"], "base_model": "tyzhu/lmind_nq_train600_eval300_v1_docidx_gpt2-xl", "model-index": [{"name": "lmind_nq_train600_eval300_v1_qa_tyzhu_lmind_nq_train600_eval300_v1_docidx_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train600_eval300_v1_qa", "type": "tyzhu/lmind_nq_train600_eval300_v1_qa"}, "metrics": [{"type": "accuracy", "value": 0.44387096774193546, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train600_eval300_v1_qa base_model:tyzhu/lmind_nq_train600_eval300_v1_docidx_gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us