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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: 22_12_13_luther_blocks_xl_fp16_5ep |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# 22_12_13_luther_blocks_xl_fp16_5ep |
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This model is a fine-tuned version of [malteos/gpt2-xl-wechsel-german](https://huggingface.co/malteos/gpt2-xl-wechsel-german) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8833 |
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- Accuracy: 0.4196 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.19 | 50 | 3.0276 | 0.3997 | |
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| No log | 0.38 | 100 | 2.9185 | 0.4143 | |
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| No log | 0.58 | 150 | 2.8846 | 0.4189 | |
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| No log | 0.77 | 200 | 2.8833 | 0.4196 | |
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| 3.0309 | 0.96 | 250 | 2.8833 | 0.4196 | |
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| 3.0309 | 1.15 | 300 | 2.8833 | 0.4196 | |
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| 3.0309 | 1.35 | 350 | 2.8833 | 0.4196 | |
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| 3.0309 | 1.54 | 400 | 2.8833 | 0.4196 | |
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| 3.0309 | 1.73 | 450 | 2.8833 | 0.4196 | |
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| 2.8083 | 1.92 | 500 | 2.8833 | 0.4196 | |
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| 2.8083 | 2.12 | 550 | 2.8833 | 0.4196 | |
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| 2.8083 | 2.31 | 600 | 2.8833 | 0.4196 | |
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| 2.8083 | 2.5 | 650 | 2.8833 | 0.4196 | |
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| 2.8083 | 2.69 | 700 | 2.8833 | 0.4196 | |
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| 2.7992 | 2.88 | 750 | 2.8833 | 0.4196 | |
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| 2.7992 | 3.08 | 800 | 2.8833 | 0.4196 | |
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| 2.7992 | 3.27 | 850 | 2.8833 | 0.4196 | |
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| 2.7992 | 3.46 | 900 | 2.8833 | 0.4196 | |
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| 2.7992 | 3.65 | 950 | 2.8833 | 0.4196 | |
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| 2.7935 | 3.85 | 1000 | 2.8833 | 0.4196 | |
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| 2.7935 | 4.04 | 1050 | 2.8833 | 0.4196 | |
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| 2.7935 | 4.23 | 1100 | 2.8833 | 0.4196 | |
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| 2.7935 | 4.42 | 1150 | 2.8833 | 0.4196 | |
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| 2.7935 | 4.62 | 1200 | 2.8833 | 0.4196 | |
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| 2.8129 | 4.81 | 1250 | 2.8833 | 0.4196 | |
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| 2.8129 | 5.0 | 1300 | 2.8833 | 0.4196 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0 |
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- Datasets 2.7.1 |
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- Tokenizers 0.12.1 |
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