Finished training.
Browse files- .gitattributes +1 -0
- README.md +81 -0
- adapter_config.json +27 -0
- adapter_model.safetensors +3 -0
- special_tokens_map.json +51 -0
- tokenizer.json +3 -0
- tokenizer_config.json +54 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: mit
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library_name: peft
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tags:
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- parquet
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- text-classification
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datasets:
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- tweet_eval
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metrics:
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- accuracy
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base_model: saattrupdan/job-listing-relevance-model
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model-index:
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- name: saattrupdan_job-listing-relevance-model-finetuned-lora-tweet_eval_emotion
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results:
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- task:
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type: text-classification
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name: Text Classification
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dataset:
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name: tweet_eval
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type: tweet_eval
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config: emotion
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split: validation
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args: emotion
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metrics:
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- type: accuracy
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value: 0.6229946524064172
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name: accuracy
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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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# saattrupdan_job-listing-relevance-model-finetuned-lora-tweet_eval_emotion
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This model is a fine-tuned version of [saattrupdan/job-listing-relevance-model](https://huggingface.co/saattrupdan/job-listing-relevance-model) on the tweet_eval dataset.
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It achieves the following results on the evaluation set:
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- accuracy: 0.6230
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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: 0.0004
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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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- 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: 4
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### Training results
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| accuracy | train_loss | epoch |
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|:--------:|:----------:|:-----:|
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| 0.0749 | None | 0 |
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| 0.4866 | 1.2982 | 0 |
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| 0.5749 | 1.1258 | 1 |
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| 0.6471 | 1.0076 | 2 |
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| 0.6230 | 0.9434 | 3 |
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### Framework versions
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- PEFT 0.8.2
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- Transformers 4.37.2
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- Pytorch 2.2.0
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- Datasets 2.16.1
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- Tokenizers 0.15.2
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "saattrupdan/job-listing-relevance-model",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 1,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 1,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"value",
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"query"
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],
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"task_type": "SEQ_CLS",
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e9a463f3b196d04a52dc4c6504d4fcedf3a0262580339d735a1eb10bbb991a7b
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size 2529464
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special_tokens_map.json
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:9a4661b2cb6b8a1007906509fe18cbfbc03062a086102bf7b80cfedb80f16c37
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size 17082854
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tokenizer_config.json
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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