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# lmind_nq_train600_eval300_v1_reciteonly_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_reciteonly_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3775
- Accuracy: 0.8392

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9083        | 0.5   | 19   | 0.4798          | 0.8220   |
| 0.3812        | 1.0   | 38   | 0.3121          | 0.8403   |
| 0.3005        | 1.5   | 57   | 0.3055          | 0.8405   |
| 0.2931        | 2.0   | 76   | 0.2985          | 0.8407   |
| 0.1987        | 2.5   | 95   | 0.3209          | 0.8393   |
| 0.195         | 3.0   | 114  | 0.3156          | 0.8404   |
| 0.1415        | 3.5   | 133  | 0.3384          | 0.8399   |
| 0.1435        | 4.0   | 152  | 0.3361          | 0.8397   |
| 0.1013        | 4.5   | 171  | 0.3542          | 0.8398   |
| 0.1041        | 5.0   | 190  | 0.3480          | 0.8399   |
| 0.0812        | 5.5   | 209  | 0.3650          | 0.8387   |
| 0.0855        | 6.0   | 228  | 0.3609          | 0.8398   |
| 0.0737        | 6.5   | 247  | 0.3678          | 0.8388   |
| 0.0737        | 7.0   | 266  | 0.3646          | 0.8390   |
| 0.0651        | 7.5   | 285  | 0.3780          | 0.8384   |
| 0.0682        | 8.0   | 304  | 0.3695          | 0.8394   |
| 0.0573        | 8.5   | 323  | 0.3794          | 0.8394   |
| 0.0662        | 9.0   | 342  | 0.3741          | 0.8397   |
| 0.0633        | 9.5   | 361  | 0.3854          | 0.8391   |
| 0.0686        | 10.0  | 380  | 0.3775          | 0.8392   |


### 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_reciteonly_qa"], "metrics": ["accuracy"], "base_model": "tyzhu/lmind_nq_train600_eval300_v1_docidx_gpt2-xl", "model-index": [{"name": "lmind_nq_train600_eval300_v1_reciteonly_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_reciteonly_qa", "type": "tyzhu/lmind_nq_train600_eval300_v1_reciteonly_qa"}, "metrics": [{"type": "accuracy", "value": 0.8392287581699346, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train600_eval300_v1_reciteonly_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