End of training

README.md

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+---
+license: cc-by-4.0
+base_model: Goader/liberta-large
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: liberta-large-topic_classification
+  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. -->
+
+# liberta-large-topic_classification
+
+This model is a fine-tuned version of [Goader/liberta-large](https://huggingface.co/Goader/liberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7957
+- Precision: 0.9167
+- Recall: 0.8749
+- F1: 0.8889
+- Accuracy: 0.8971
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 88   | 0.7214          | 0.8294    | 0.7438 | 0.7532 | 0.7843   |
+| No log        | 2.0   | 176  | 0.6388          | 0.8181    | 0.7797 | 0.7826 | 0.8088   |
+| No log        | 3.0   | 264  | 0.8149          | 0.8625    | 0.8692 | 0.8617 | 0.8725   |
+| No log        | 4.0   | 352  | 0.8210          | 0.9171    | 0.8603 | 0.8695 | 0.8824   |
+| No log        | 5.0   | 440  | 0.7850          | 0.9173    | 0.8700 | 0.8841 | 0.8922   |
+| 0.3285        | 6.0   | 528  | 0.7936          | 0.8987    | 0.8670 | 0.8770 | 0.8824   |
+| 0.3285        | 7.0   | 616  | 0.7794          | 0.9217    | 0.8749 | 0.8913 | 0.8971   |
+| 0.3285        | 8.0   | 704  | 0.7835          | 0.9217    | 0.8749 | 0.8913 | 0.8971   |
+| 0.3285        | 9.0   | 792  | 0.7947          | 0.9167    | 0.8749 | 0.8889 | 0.8971   |
+| 0.3285        | 10.0  | 880  | 0.7957          | 0.9167    | 0.8749 | 0.8889 | 0.8971   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 1.11.0a0+17540c5
+- Datasets 2.21.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "Goader/liberta-large",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "sep_token_id": 3,
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32000
+}

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