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--- |
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base_model: albert/albert-xxlarge-v2 |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: albert-xxlarge-v2-Adapters_2 |
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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/dhanishetty-personaluse/huggingface/runs/uwrexp6u) |
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# albert-xxlarge-v2-Adapters_2 |
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This model is a fine-tuned version of [albert/albert-xxlarge-v2](https://huggingface.co/albert/albert-xxlarge-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5145 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: inverse_sqrt |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.1194 | 0.2291 | 50 | 1.1023 | |
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| 1.0831 | 0.4582 | 100 | 1.0770 | |
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| 1.0148 | 0.6873 | 150 | 0.9637 | |
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| 0.9064 | 0.9164 | 200 | 0.8538 | |
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| 0.7693 | 1.1455 | 250 | 0.7700 | |
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| 0.7445 | 1.3746 | 300 | 0.7098 | |
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| 0.7045 | 1.6037 | 350 | 0.6914 | |
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| 0.6733 | 1.8328 | 400 | 0.6374 | |
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| 0.6239 | 2.0619 | 450 | 0.6226 | |
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| 0.6208 | 2.2910 | 500 | 0.5913 | |
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| 0.6153 | 2.5200 | 550 | 0.5811 | |
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| 0.591 | 2.7491 | 600 | 0.5630 | |
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| 0.5894 | 2.9782 | 650 | 0.5500 | |
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| 0.5788 | 3.2073 | 700 | 0.5461 | |
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| 0.5187 | 3.4364 | 750 | 0.5353 | |
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| 0.5271 | 3.6655 | 800 | 0.5386 | |
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| 0.5812 | 3.8946 | 850 | 0.5309 | |
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| 0.5532 | 4.1237 | 900 | 0.5296 | |
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| 0.5602 | 4.3528 | 950 | 0.5204 | |
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| 0.5209 | 4.5819 | 1000 | 0.5144 | |
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| 0.5579 | 4.8110 | 1050 | 0.5145 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.4 |
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- Pytorch 2.1.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
