End of training

README.md

@@ -0,0 +1,72 @@
+---
+license: mit
+base_model: joeddav/xlm-roberta-large-xnli
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: xlm-roberta-large-xnli-v5.0
+  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. -->
+
+# xlm-roberta-large-xnli-v5.0
+
+This model is a fine-tuned version of [joeddav/xlm-roberta-large-xnli](https://huggingface.co/joeddav/xlm-roberta-large-xnli) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4987
+- F1 Macro: 0.8279
+- F1 Micro: 0.8288
+- Accuracy Balanced: 0.8278
+- Accuracy: 0.8288
+- Precision Macro: 0.8281
+- Recall Macro: 0.8278
+- Precision Micro: 0.8288
+- Recall Micro: 0.8288
+
+## 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: 9e-06
+- train_batch_size: 8
+- eval_batch_size: 64
+- seed: 40
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.06
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
+| 0.3851        | 0.85  | 200  | 0.4586          | 0.8017   | 0.8025   | 0.8029            | 0.8025   | 0.8012          | 0.8029       | 0.8025          | 0.8025       |
+| 0.2689        | 1.69  | 400  | 0.4498          | 0.8137   | 0.8147   | 0.8145            | 0.8147   | 0.8133          | 0.8145       | 0.8147          | 0.8147       |
+| 0.194         | 2.54  | 600  | 0.5334          | 0.8244   | 0.8253   | 0.8252            | 0.8253   | 0.8239          | 0.8252       | 0.8253          | 0.8253       |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.5.1+cu121
+- Datasets 2.14.7
+- Tokenizers 0.13.3

config.json

@@ -30,7 +30,7 @@
   "pad_token_id": 1,
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
-  "torch_dtype": "float32",
+  "torch_dtype": "float16",
   "transformers_version": "4.33.3",
   "type_vocab_size": 1,
   "use_cache": true,

pytorch_model.bin

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-size 2239705966
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+size 1119921006