End of training

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,74 @@
+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: populism_classifier_bsample_111
+  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. -->
+
+# populism_classifier_bsample_111
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3306
+- Accuracy: 0.8813
+- 1-f1: 0.3077
+- 1-recall: 0.9091
+- 1-precision: 0.1852
+- Balanced Acc: 0.8948
+
+## 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: 3e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
+| 0.7516        | 1.0   | 10   | 0.6561          | 0.9631   | 0.0    | 0.0      | 0.0         | 0.4959       |
+| 0.6877        | 2.0   | 20   | 0.5274          | 0.9710   | 0.0    | 0.0      | 0.0         | 0.5          |
+| 0.6049        | 3.0   | 30   | 0.5956          | 0.8707   | 0.1967 | 0.5455   | 0.12        | 0.7129       |
+| 0.5518        | 4.0   | 40   | 0.4287          | 0.8206   | 0.2093 | 0.8182   | 0.12        | 0.8194       |
+| 0.4657        | 5.0   | 50   | 0.5567          | 0.7018   | 0.1630 | 1.0      | 0.0887      | 0.8465       |
+| 0.5129        | 6.0   | 60   | 0.2019          | 0.9261   | 0.3636 | 0.7273   | 0.2424      | 0.8297       |
+| 0.4573        | 7.0   | 70   | 0.1564          | 0.8997   | 0.3214 | 0.8182   | 0.2         | 0.8602       |
+| 0.2978        | 8.0   | 80   | 0.3465          | 0.8971   | 0.3158 | 0.8182   | 0.1957      | 0.8588       |
+| 0.1075        | 9.0   | 90   | 0.3306          | 0.8813   | 0.3077 | 0.9091   | 0.1852      | 0.8948       |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.4.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

config.json

@@ -0,0 +1,29 @@
+{
+  "_name_or_path": "FacebookAI/xlm-roberta-large",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.2,
+  "bos_token_id": 0,
+  "classifier_dropout": 0.2,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.2,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

model.safetensors

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special_tokens_map.json

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tokenizer.json

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tokenizer_config.json

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+  "model_max_length": 512,
+  "pad_token": "<pad>",
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+  "tokenizer_class": "XLMRobertaTokenizer",
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+}

training_args.bin

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