End of training

README.md

@@ -0,0 +1,60 @@
+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: robertolli
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# robertolli
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 3.2551
+- eval_accuracy: 0.0415
+- eval_f1: 0.0033
+- eval_runtime: 1781.7772
+- eval_samples_per_second: 58.722
+- eval_steps_per_second: 0.196
+- step: 0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 300
+- eval_batch_size: 300
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 600
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 7
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0
+- Datasets 2.21.0
+- Tokenizers 0.19.1

config.json

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   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
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+  "transformers_version": "4.44.0",
   "type_vocab_size": 1,
   "use_cache": true,
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special_tokens_map.json

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+}

tokenizer_config.json

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+  "added_tokens_decoder": {
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+  "errors": "replace",
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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