Training in progress epoch 0

README.md

@@ -5,12 +5,6 @@ tags:
 model-index:
 - name: n3wtou/mt5-small-finedtuned-4-swahili
   results: []
-datasets:
-- csebuetnlp/xlsum
-language:
-- sw
-metrics:
-- rouge
 ---
 
 <!-- This model card has been generated automatically according to the information Keras had access to. You should
@@ -18,15 +12,15 @@ probably proofread and complete it, then remove this comment. -->
 
 # n3wtou/mt5-small-finedtuned-4-swahili
 
-This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the [csebuetnlp/xlsum](https://huggingface.co/datasets/csebuetnlp/xlsum/viewer/swahili/train) dataset.
+This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 3.0006
-- Validation Loss: 2.7015
-- Epoch: 9
+- Train Loss: 7.7378
+- Validation Loss: 4.4308
+- Epoch: 0
 
 ## Model description
 
-This model is a fined-tuned google/mt5-small for Kiswahili abstractive text generation
+More information needed
 
 ## Intended uses & limitations
 
@@ -41,23 +35,14 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0003, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0003, 'decay_steps': 9900, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 100, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
+- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0003, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0003, 'decay_steps': 99900, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 100, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
 - training_precision: mixed_float16
 
 ### Training results
 
 | Train Loss | Validation Loss | Epoch |
 |:----------:|:---------------:|:-----:|
-| 7.0434     | 3.2396          | 0     |
-| 4.3604     | 3.0452          | 1     |
-| 3.9184     | 2.9186          | 2     |
-| 3.6516     | 2.8443          | 3     |
-| 3.4569     | 2.7955          | 4     |
-| 3.3146     | 2.7645          | 5     |
-| 3.2039     | 2.7292          | 6     |
-| 3.1135     | 2.7182          | 7     |
-| 3.0450     | 2.7040          | 8     |
-| 3.0006     | 2.7015          | 9     |
+| 7.7378     | 4.4308          | 0     |
 
 
 ### Framework versions
@@ -65,4 +50,4 @@ The following hyperparameters were used during training:
 - Transformers 4.29.2
 - TensorFlow 2.12.0
 - Datasets 2.12.0
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3

tf_model.h5

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tokenizer.json

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