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--- |
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license: apache-2.0 |
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base_model: google/bigbird-roberta-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bigbird-roberta-base-fineweb-edu-llama3-annotations-4096-vN |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/pszemraj/eduscore-regression/runs/04oc07hx) |
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# bigbird-roberta-base-fineweb-edu-llama3-annotations-4096-vN |
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This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on the HuggingFaceFW/fineweb-edu-llama3-annotations dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2176 |
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- Mse: 0.2176 |
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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: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 90085 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-09 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 0.4763 | 0.0288 | 100 | 0.4468 | 0.4468 | |
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| 0.3078 | 0.0577 | 200 | 0.3130 | 0.3130 | |
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| 0.3088 | 0.0865 | 300 | 0.2695 | 0.2695 | |
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| 0.2379 | 0.1153 | 400 | 0.2618 | 0.2618 | |
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| 0.289 | 0.1441 | 500 | 0.2583 | 0.2583 | |
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| 0.3049 | 0.1730 | 600 | 0.2723 | 0.2723 | |
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| 0.2292 | 0.2018 | 700 | 0.2477 | 0.2477 | |
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| 0.2677 | 0.2306 | 800 | 0.2369 | 0.2369 | |
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| 0.3181 | 0.2594 | 900 | 0.2307 | 0.2307 | |
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| 0.2551 | 0.2883 | 1000 | 0.2411 | 0.2411 | |
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| 0.2743 | 0.3171 | 1100 | 0.2350 | 0.2350 | |
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| 0.2383 | 0.3459 | 1200 | 0.2424 | 0.2424 | |
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| 0.2191 | 0.3747 | 1300 | 0.2279 | 0.2279 | |
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| 0.2431 | 0.4036 | 1400 | 0.2232 | 0.2232 | |
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| 0.2161 | 0.4324 | 1500 | 0.2307 | 0.2307 | |
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| 0.2459 | 0.4612 | 1600 | 0.2246 | 0.2246 | |
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| 0.2403 | 0.4900 | 1700 | 0.2232 | 0.2232 | |
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| 0.251 | 0.5189 | 1800 | 0.2421 | 0.2421 | |
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| 0.2565 | 0.5477 | 1900 | 0.2207 | 0.2207 | |
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| 0.2274 | 0.5765 | 2000 | 0.2294 | 0.2294 | |
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| 0.2272 | 0.6053 | 2100 | 0.2192 | 0.2192 | |
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| 0.2668 | 0.6342 | 2200 | 0.2204 | 0.2204 | |
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| 0.2434 | 0.6630 | 2300 | 0.2196 | 0.2196 | |
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| 0.2464 | 0.6918 | 2400 | 0.2185 | 0.2185 | |
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| 0.2338 | 0.7206 | 2500 | 0.2166 | 0.2166 | |
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| 0.243 | 0.7495 | 2600 | 0.2165 | 0.2165 | |
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| 0.1891 | 0.7783 | 2700 | 0.2201 | 0.2201 | |
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| 0.2355 | 0.8071 | 2800 | 0.2167 | 0.2167 | |
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| 0.2231 | 0.8359 | 2900 | 0.2168 | 0.2168 | |
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| 0.2274 | 0.8648 | 3000 | 0.2243 | 0.2243 | |
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| 0.2287 | 0.8936 | 3100 | 0.2203 | 0.2203 | |
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| 0.261 | 0.9224 | 3200 | 0.2186 | 0.2186 | |
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| 0.2187 | 0.9512 | 3300 | 0.2176 | 0.2176 | |
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| 0.2069 | 0.9801 | 3400 | 0.2178 | 0.2178 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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