Instructions to use MikeGreen2710/training_with_callbacks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MikeGreen2710/training_with_callbacks with Transformers:
# Load model directly from transformers import AutoTokenizer, CustomSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MikeGreen2710/training_with_callbacks") model = CustomSequenceClassification.from_pretrained("MikeGreen2710/training_with_callbacks", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MikeGreen2710/model_location_with_extra_16_features
Browse files- README.md +79 -0
- config.json +30 -0
- model.safetensors +3 -0
- runs/Apr01_04-00-49_ece4728d2eeb/events.out.tfevents.1711944054.ece4728d2eeb.4936.0 +3 -0
- runs/Apr01_04-26-36_ece4728d2eeb/events.out.tfevents.1711945608.ece4728d2eeb.4936.1 +3 -0
- runs/Apr01_05-21-01_ece4728d2eeb/events.out.tfevents.1711948869.ece4728d2eeb.4936.2 +3 -0
- runs/Apr01_09-07-03_ece4728d2eeb/events.out.tfevents.1711962431.ece4728d2eeb.4936.3 +3 -0
- runs/Apr01_09-07-41_ece4728d2eeb/events.out.tfevents.1711962467.ece4728d2eeb.4936.4 +3 -0
- runs/Apr01_09-35-40_ece4728d2eeb/events.out.tfevents.1711964143.ece4728d2eeb.4936.5 +3 -0
- runs/Apr02_00-58-37_49fd5aaf7c90/events.out.tfevents.1712019521.49fd5aaf7c90.6589.0 +3 -0
- runs/Apr02_01-00-50_49fd5aaf7c90/events.out.tfevents.1712019654.49fd5aaf7c90.9353.0 +3 -0
- runs/Apr02_01-23-07_49fd5aaf7c90/events.out.tfevents.1712020997.49fd5aaf7c90.9353.1 +3 -0
- runs/Apr02_02-27-40_49fd5aaf7c90/events.out.tfevents.1712024868.49fd5aaf7c90.9353.2 +3 -0
- runs/Apr02_02-31-54_49fd5aaf7c90/events.out.tfevents.1712025118.49fd5aaf7c90.9353.3 +3 -0
- runs/Apr18_09-33-52_972f59438847/events.out.tfevents.1713432837.972f59438847.5126.0 +3 -0
- runs/Apr18_10-01-28_972f59438847/events.out.tfevents.1713434491.972f59438847.5126.1 +3 -0
- runs/Apr18_11-31-48_972f59438847/events.out.tfevents.1713439913.972f59438847.5126.2 +3 -0
- training_args.bin +3 -0
README.md
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---
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base_model: MikeGreen2710/mlm_listing_1.79
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tags:
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- generated_from_trainer
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metrics:
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- f1
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model-index:
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- name: training_with_callbacks
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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/ommlops/huggingface/runs/cib2hyrr)
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# training_with_callbacks
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This model is a fine-tuned version of [MikeGreen2710/mlm_listing_1.79](https://huggingface.co/MikeGreen2710/mlm_listing_1.79) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6543
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- F1: 0.9208
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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: 24
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- eval_batch_size: 12
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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: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.0824 | 1.0 | 450 | 0.3580 | 0.9060 |
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| 0.0511 | 2.0 | 900 | 0.4426 | 0.9124 |
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| 0.026 | 3.0 | 1350 | 0.5414 | 0.9068 |
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| 0.0217 | 4.0 | 1800 | 0.5045 | 0.9143 |
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| 0.0173 | 5.0 | 2250 | 0.5599 | 0.9118 |
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| 0.0118 | 6.0 | 2700 | 0.6114 | 0.9149 |
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| 0.0064 | 7.0 | 3150 | 0.6536 | 0.9134 |
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| 0.0113 | 8.0 | 3600 | 0.7119 | 0.9011 |
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| 0.0075 | 9.0 | 4050 | 0.6683 | 0.9124 |
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| 0.0069 | 10.0 | 4500 | 0.6543 | 0.9208 |
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| 0.0042 | 11.0 | 4950 | 0.6937 | 0.9158 |
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| 0.0062 | 12.0 | 5400 | 0.7119 | 0.9184 |
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| 0.0048 | 13.0 | 5850 | 0.7300 | 0.9143 |
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| 0.0021 | 14.0 | 6300 | 0.7877 | 0.9110 |
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| 0.0032 | 15.0 | 6750 | 0.7892 | 0.9116 |
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| 0.003 | 16.0 | 7200 | 0.7744 | 0.9091 |
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| 0.0069 | 17.0 | 7650 | 0.7118 | 0.9184 |
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| 0.0006 | 18.0 | 8100 | 0.7633 | 0.9143 |
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| 0.0011 | 19.0 | 8550 | 0.7438 | 0.9200 |
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| 0.0001 | 20.0 | 9000 | 0.7461 | 0.9200 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "MikeGreen2710/mlm_listing_1.79",
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"architectures": [
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"CustomSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 258,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"tokenizer_class": "PhobertTokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.42.4",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 64001
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}
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