Training in progress, step 61875
Browse files- README.md +60 -134
- logs/attn_loss_fn=cos, attn_weight=25.0, layer_mapper=layer-2, projector=linear/events.out.tfevents.1724395244.e3f806ea38c9 +3 -0
- logs/attn_loss_fn=cos, attn_weight=25.0, layer_mapper=layer-2, projector=linear/events.out.tfevents.1724395600.e3f806ea38c9 +3 -0
- logs/attn_loss_fn=kl, attn_weight=5, layer_mapper=all, projector=linear/events.out.tfevents.1724395297.e3f806ea38c9 +3 -0
- model.safetensors +1 -1
- training_args.bin +2 -2
README.md
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---
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datasets:
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- wikimedia/wikipedia
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library_name: Distily
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license: mit
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tags:
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- bitnet
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- 1.58b
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results: []
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---
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#
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should probably proofread and complete it, then remove this comment.
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More information needed
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More information needed
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- **Data Type (dtype)**: torch.bfloat16
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- **Model Size**: 0.24 GB
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# Evaluation Metrics Comparison
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| step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | tinystoriesppl | zhwikippl |
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| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
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| **teacher eval** | | 43.25 | 61.25 | | | | | 11.6875 | 19.125 |
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| 0 | 0 | 2473901162496.0 | 170424302305280.0 | 25.7744 | 25.131 | 99.479 | 12.455 | 4060086272.0 | 71468255805440.0 |
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| 2500 | 0.0404 | 960.0 | 8064.0 | 6.1231 | 25.2285 | 99.094 | 12.407 | 652.0 | 6816.0 |
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| 5000 | 0.0808 | 380.0 | 1896.0 | 5.0307 | 25.2563 | 98.985 | 12.393 | 270.0 | 286.0 |
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| 7500 | 0.1212 | 230.0 | 824.0 | 4.5129 | 25.128 | 99.491 | 12.456 | 202.0 | 174.0 |
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| 10000 | 0.1616 | 171.0 | 628.0 | 4.2261 | 25.2755 | 98.91 | 12.384 | 151.0 | 173.0 |
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| 12500 | 0.2020 | 126.5 | 482.0 | 3.8533 | 25.2021 | 99.198 | 12.42 | 106.0 | 156.0 |
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| 15000 | 0.2424 | 109.5 | 430.0 | 3.6650 | 25.2487 | 99.015 | 12.397 | 88.0 | 155.0 |
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| 17500 | 0.2828 | 93.0 | 350.0 | 3.5198 | 25.1751 | 99.305 | 12.433 | 73.5 | 119.0 |
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| 20000 | 0.3232 | 77.5 | 282.0 | 3.3352 | 25.2573 | 98.981 | 12.392 | 63.25 | 135.0 |
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| 22500 | 0.3636 | 66.5 | 213.0 | 3.1511 | 25.1782 | 99.292 | 12.431 | 50.75 | 80.0 |
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| 25000 | 0.4040 | 63.25 | 197.0 | 3.0803 | 25.2258 | 99.105 | 12.408 | 44.5 | 80.5 |
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| 27500 | 0.4444 | 58.5 | 212.0 | 3.0299 | 25.2357 | 99.066 | 12.403 | 41.75 | 68.5 |
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| 30000 | 0.4848 | 58.5 | 202.0 | 3.0169 | 25.2481 | 99.017 | 12.397 | 43.25 | 91.5 |
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| 32500 | 0.5253 | 58.75 | 173.0 | 3.0014 | 25.2575 | 98.981 | 12.392 | 41.5 | 62.75 |
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| 35000 | 0.5657 | 57.25 | 164.0 | 2.9385 | 25.2523 | 99.001 | 12.395 | 38.0 | 49.0 |
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| 37500 | 0.6061 | 57.0 | 157.0 | 2.9163 | 25.1539 | 99.388 | 12.443 | 39.25 | 61.75 |
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| 40000 | 0.6465 | 54.75 | 172.0 | 2.8984 | 25.2388 | 99.054 | 12.402 | 35.0 | 67.5 |
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| 42500 | 0.6869 | 53.0 | 151.0 | 2.8789 | 25.2418 | 99.042 | 12.4 | 35.25 | 49.75 |
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| 45000 | 0.7273 | 49.5 | 134.0 | 2.7753 | 25.2511 | 99.005 | 12.395 | 30.25 | 42.25 |
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| 47500 | 0.7677 | 50.0 | 124.0 | 2.7506 | 25.2475 | 99.02 | 12.397 | 29.5 | 38.75 |
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| 50000 | 0.8081 | 49.0 | 124.5 | 2.7361 | 25.2146 | 99.149 | 12.413 | 28.75 | 38.25 |
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| 52500 | 0.8485 | 48.25 | 120.0 | 2.7262 | 25.1855 | 99.264 | 12.428 | 29.125 | 35.0 |
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| 55000 | 0.8889 | 47.75 | 117.0 | 2.7099 | 25.2332 | 99.076 | 12.404 | 28.25 | 33.0 |
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| 57500 | 0.9293 | 47.25 | 117.5 | 2.7045 | 25.2693 | 98.934 | 12.387 | 28.0 | 32.5 |
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| 60000 | 0.9697 | 47.25 | 116.5 | 2.7013 | 25.2549 | 98.991 | 12.394 | 27.875 | 32.25 |
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| 61875 | 1.0 | 47.25 | 116.5 | 2.7009 | 25.2212 | 99.123 | 12.41 | 28.0 | 32.25 |
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# Resource Usage Comparison
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- VRAM Use: 7.7830 GB
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# Distillation (Teacher -> Student) Architecture Difference:
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- **Architecture**: `GPT2LMHeadModel` -> `GPT2LMHeadModel`
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- **Total Parameters**: 124,439,808 -> 124,439,808
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- **Data Type (dtype)**: torch.bfloat16 -> torch.bfloat16
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- **Model Size**: 0.24 GB -> 0.24 GB
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<details>
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<summary>Module Diff Details</summary>
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```diff
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```
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</details>
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<br/>
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# Train Dataset
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Trained on 145,744,973 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
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- Num Samples: `247,500`
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- Subset: `20231101.en`
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- Split: `train`
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# Training Objective
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```
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DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5, loss_fn=cos, layer_mapper=layer-2))
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```
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# Hyperparameters
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The following hyperparameters were used during training:
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<details>
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<summary>Expand</summary>
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- learning_rate: `0.0001`
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- train_batch_size: `4`
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- eval_batch_size: `8`
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- seed: `42`
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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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- lr_scheduler_warmup_ratio: `0.5`
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- num_epochs: `1.0`
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- distillation_objective: `DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5, loss_fn=cos, layer_mapper=layer-2))`
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- train_embeddings: `True`
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- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7f14d416e830>`
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- student_model_name_or_path: `None`
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- student_config_name_or_path: `None`
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- student_model_config: `None`
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- reinitialize_weights: `None`
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- copy_teacher_modules: `[('lm_head', False)]`
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- student_model_as_bitnet: `True`
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- student_model_compile: `False`
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- dropout: `None`
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- teacher_model_name_or_path: `gpt2`
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- teacher_load_in_8bit: `False`
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- teacher_load_in_4bit: `False`
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- teacher_model_compile: `False`
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- dataset_uri: `wikimedia/wikipedia`
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- dataset_subset: `20231101.en`
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- dataset_split: `train`
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- dataset_column_name: `text`
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- dataset_sample_size: `250000`
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- dataset_test_size: `0.01`
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- gradient_accumulation_steps: `1`
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- weight_decay: `0.0`
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- max_grad_norm: `1.0`
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- warmup_ratio: `0.5`
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- warmup_steps: `0`
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- gradient_checkpointing: `True`
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</details>
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<br/>
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# Framework Versions
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- Distily 0.2.0
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- Transformers 4.44.1
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- Pytorch 2.5.0.dev20240821+cu121
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- Datasets 2.21.0
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library_name: transformers
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license: mit
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base_model: gpt2
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tags:
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- bitnet
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- 1.58b
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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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# distily_multi_experiment
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 11.8595
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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: 0.0001
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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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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- lr_scheduler_warmup_ratio: 0.5
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- num_epochs: 1.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:-----:|:---------------:|
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| No log | 0 | 0 | 45.5392 |
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| 19.25 | 0.0404 | 2500 | 20.5160 |
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| 17.0 | 0.0808 | 5000 | 18.1646 |
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| 16.375 | 0.1212 | 7500 | 16.8100 |
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| 18.5 | 0.1616 | 10000 | 15.9662 |
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| 18.125 | 0.2020 | 12500 | 14.8913 |
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| 16.125 | 0.2424 | 15000 | 14.2909 |
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| 13.875 | 0.2828 | 17500 | 13.9054 |
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| 12.5625 | 0.3232 | 20000 | 13.4260 |
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| 13.8125 | 0.3636 | 22500 | 12.9026 |
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| 14.5625 | 0.4040 | 25000 | 12.6783 |
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| 15.1875 | 0.4444 | 27500 | 12.5651 |
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| 13.4375 | 0.4848 | 30000 | 12.5742 |
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| 6.8125 | 0.5253 | 32500 | 12.5106 |
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| 12.0 | 0.5657 | 35000 | 12.3849 |
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| 13.9375 | 0.6061 | 37500 | 12.3297 |
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| 5.375 | 0.6465 | 40000 | 12.2764 |
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| 20.625 | 0.6869 | 42500 | 12.2612 |
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| 10.0 | 0.7273 | 45000 | 12.0058 |
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| 18.75 | 0.7677 | 47500 | 11.9614 |
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| 10.0625 | 0.8081 | 50000 | 11.9339 |
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| 16.0 | 0.8485 | 52500 | 11.9123 |
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| 18.625 | 0.8889 | 55000 | 11.8770 |
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| 15.875 | 0.9293 | 57500 | 11.8680 |
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| 11.25 | 0.9697 | 60000 | 11.8611 |
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### Framework versions
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- Transformers 4.44.1
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- Pytorch 2.5.0.dev20240821+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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logs/attn_loss_fn=cos, attn_weight=25.0, layer_mapper=layer-2, projector=linear/events.out.tfevents.1724395244.e3f806ea38c9
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