varun-v-rao
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End of training
Browse files
README.md
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---
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license: mit
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base_model: openai-community/gpt2
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tags:
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- generated_from_trainer
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datasets:
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- stanfordnlp/snli
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metrics:
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- accuracy
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model-index:
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- name: gpt2-lora-592K-snli-model2
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: snli
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type: stanfordnlp/snli
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7926234505181874
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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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# gpt2-lora-592K-snli-model2
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This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the snli dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5249
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- Accuracy: 0.7926
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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: 2e-05
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- train_batch_size: 256
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- eval_batch_size: 128
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- seed: 10
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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: 3
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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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| 0.7231 | 1.0 | 2146 | 0.5854 | 0.7600 |
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| 0.6412 | 2.0 | 4292 | 0.5355 | 0.7867 |
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| 0.6266 | 3.0 | 6438 | 0.5249 | 0.7926 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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adapter_model.safetensors
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config.json
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{
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"_name_or_path": "openai-community/gpt2",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2ForSequenceClassification"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 768,
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"n_head": 12,
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"n_inner": null,
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"n_layer": 12,
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"n_positions": 1024,
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"pad_token_id": 50256,
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"problem_type": "single_label_classification",
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"task_specific_params": {
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"text-generation": {
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"do_sample": true,
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"max_length": 50
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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"use_cache": true,
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"vocab_size": 50257
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}
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model.safetensors
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size 497783504
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runs/Jun19_23-12-50_gl1510.arc-ts.umich.edu/events.out.tfevents.1718853176.gl1510.arc-ts.umich.edu.4074931.1
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