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afaranda
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my_awesome_geopolitical_model

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
Model card Files Community
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Files changed (8) hide show
  1. README.md +82 -0
  2. config.json +33 -0
  3. generation_config.json +6 -0
  4. pytorch_model.bin +3 -0
  5. special_tokens_map.json +107 -0
  6. tokenizer.json +0 -0
  7. tokenizer_config.json +111 -0
  8. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: gsarti/it5-small
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - geopolitica
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: my_awesome_geopolitical_model
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+ results:
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+ - task:
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+ name: Sequence-to-sequence Language Modeling
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+ type: text2text-generation
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+ dataset:
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+ name: geopolitica
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+ type: geopolitica
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.2106
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+ ---
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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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+
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+ # my_awesome_geopolitical_model
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+
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+ This model is a fine-tuned version of [gsarti/it5-small](https://huggingface.co/gsarti/it5-small) on the geopolitica dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: nan
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+ - Rouge1: 0.2106
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+ - Rouge2: 0.0906
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+ - Rougel: 0.2106
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+ - Rougelsum: 0.2106
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+ - Gen Len: 19.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 16
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 1 | nan | 0.2106 | 0.0906 | 0.2106 | 0.2106 | 19.0 |
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+ | No log | 2.0 | 2 | nan | 0.2106 | 0.0906 | 0.2106 | 0.2106 | 19.0 |
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+ | No log | 3.0 | 3 | nan | 0.2106 | 0.0906 | 0.2106 | 0.2106 | 19.0 |
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+ | No log | 4.0 | 4 | nan | 0.2106 | 0.0906 | 0.2106 | 0.2106 | 19.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.3
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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+ "T5ForConditionalGeneration"
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+ ],
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+ "dense_act_fn": "gelu_new",
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+ "torch_dtype": "float32",
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+ "use_cache": true,
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+ "vocab_size": 32103
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+ }
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