Training in progress, step 125

README.md

@@ -1,84 +1,75 @@
----
-library_name: transformers
-base_model: distilbert-base-uncased
-tags:
-- generated_from_trainer
-metrics:
-- accuracy
-model-index:
-- name: mi-super-modelo
-  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. -->
-
-# mi-super-modelo
-
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.3257
-- Accuracy: 0.865
-
-## 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: 1
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.7019        | 0.04  | 5    | 0.6916          | 0.51     |
-| 0.7006        | 0.08  | 10   | 0.6860          | 0.495    |
-| 0.7015        | 0.12  | 15   | 0.6802          | 0.58     |
-| 0.6842        | 0.16  | 20   | 0.6756          | 0.525    |
-| 0.658         | 0.2   | 25   | 0.6492          | 0.595    |
-| 0.6329        | 0.24  | 30   | 0.5335          | 0.855    |
-| 0.4345        | 0.28  | 35   | 0.4493          | 0.825    |
-| 0.3086        | 0.32  | 40   | 0.3973          | 0.84     |
-| 0.4788        | 0.36  | 45   | 0.3747          | 0.855    |
-| 0.6449        | 0.4   | 50   | 0.4614          | 0.8      |
-| 0.2355        | 0.44  | 55   | 0.3603          | 0.855    |
-| 0.4233        | 0.48  | 60   | 0.4841          | 0.8      |
-| 0.5185        | 0.52  | 65   | 0.5940          | 0.755    |
-| 0.3089        | 0.56  | 70   | 0.3760          | 0.87     |
-| 0.3867        | 0.6   | 75   | 0.3636          | 0.86     |
-| 0.3289        | 0.64  | 80   | 0.3339          | 0.885    |
-| 0.5774        | 0.68  | 85   | 0.3070          | 0.875    |
-| 0.3258        | 0.72  | 90   | 0.4532          | 0.8      |
-| 0.5363        | 0.76  | 95   | 0.3687          | 0.86     |
-| 0.4099        | 0.8   | 100  | 0.2847          | 0.88     |
-| 0.2841        | 0.84  | 105  | 0.3147          | 0.885    |
-| 0.3949        | 0.88  | 110  | 0.3424          | 0.855    |
-| 0.3056        | 0.92  | 115  | 0.3620          | 0.835    |
-| 0.4219        | 0.96  | 120  | 0.3437          | 0.855    |
-| 0.3343        | 1.0   | 125  | 0.3257          | 0.865    |
-
-
-### Framework versions
-
-- Transformers 4.44.2
-- Pytorch 2.4.1+cpu
-- Datasets 2.21.0
-- Tokenizers 0.19.1
+---
+datasets:
+- yelp_review_full
+license: apache-2.0
+metrics:
+- accuracy
+tags:
+- generated_from_trainer
+model-index:
+- name: mi-super-modelo
+  results:
+  - task:
+      type: text-classification
+      name: Text Classification
+    dataset:
+      name: yelp_review_full
+      type: yelp_review_full
+      config: yelp_review_full
+      split: test
+      args: yelp_review_full
+    metrics:
+    - type: accuracy
+      value: 0.225
+      name: Accuracy
+---
+
+<!-- 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. -->
+
+# mi-super-modelo
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the yelp_review_full dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6404
+- Accuracy: 0.225
+
+## 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: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.7058        | 0.5   | 5    | 1.7046          | 0.225    |
+| 1.6208        | 1.0   | 10   | 1.6404          | 0.225    |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3

model.safetensors

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special_tokens_map.json

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tokenizer_config.json

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+  "pad_token": "[PAD]",
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+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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