Update README.md

README.md

@@ -46,7 +46,7 @@ model-index:
 
 ---
 
-# mt5-small_test_45
+# mt5-small
 
 This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an enhanced version of the Natural Questions dataset.
 It achieves the following results on the evaluation set:
@@ -83,6 +83,23 @@ It can give false negatives and false positives on occasion (see Training Result
 
 More information needed
 
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load model and tokenizer
+model_name = "username/model-name"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Generate text
+input_text = "Once upon a time"
+input_ids = tokenizer.encode(input_text, return_tensors="pt")
+output = model.generate(input_ids, max_length=50)
+
+print(tokenizer.decode(output[0], skip_special_tokens=True))
+```
+
 ## Training procedure
 
 ### Training hyperparameters
@@ -105,14 +122,15 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu    | Gen Len | Meteor | True negatives | False negatives | Cosine Sim |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:------:|:--------------:|:---------------:|:----------:|
 | 2.5724        | 1.0   | 175  | 0.9876          | 18.7781 | 15.6002 | 18.22   | 18.2686   | 7.6676  | 7.7661  | 0.1628 | 72.8701        | 56.677          | 0.4003     |
-| 1.1469        | 1.99  | 350  | 0.8580          | 36.8209 | 31.2514 | 35.5008 | 35.5462   | 25.7137 | 12.0014 | 0.3311 | 62.8399        | 20.3934         | 0.6645     |
+| 1.1469        | 1.99  | 350  | 0.8580          | 36.8209 | 31.2514 | 35.5008 | 35.5462   | 25.7137 | 12.0014 | 0.3311 | 62.8399        | 20.3934         | 0.66
+|
 | 0.9468        | 2.99  | 525  | 0.7997          | 40.4128 | 34.716  | 39.0867 | 39.0972   | 29.3028 | 12.4287 | 0.3656 | 63.4441        | 15.295          | 0.7114     |
 | 0.8129        | 3.98  | 700  | 0.7733          | 42.6764 | 36.7266 | 41.2465 | 41.2833   | 32.0644 | 12.9002 | 0.3871 | 62.1752        | 11.413          | 0.7425     |
 | 0.7228        | 4.98  | 875  | 0.7483          | 42.9082 | 36.957  | 41.482  | 41.5233   | 32.4942 | 12.8866 | 0.3906 | 63.3233        | 11.5166         | 0.747      |
 | 0.6493        | 5.97  | 1050 | 0.7293          | 40.3205 | 34.9632 | 39.1111 | 39.1168   | 28.8249 | 11.6867 | 0.3674 | 73.8973        | 17.9865         | 0.7068     |
 | 0.5883        | 6.97  | 1225 | 0.7172          | 42.7342 | 37.0855 | 41.4069 | 41.424    | 32.1296 | 12.48   | 0.3887 | 70.0302        | 12.7847         | 0.7392     |
 | 0.5409        | 7.96  | 1400 | 0.7387          | 44.6657 | 38.8426 | 43.3276 | 43.3496   | 34.4773 | 12.9395 | 0.4084 | 66.3444        | 9.5238          | 0.7658     |
-| 0.5035        | 8.96  | 1575 | 0.7330          | 43.4925 | 38.0013 | 42.2697 | 42.2372   | 32.6131 | 12.2789 | 0.3979 | 72.6284        | 12.8364         | 0.7451     |
+| 0.5035        | 8.96  | 1575 | 0.7330          | 43.4925 | 38.0013 | 42.2697 | 42.2372   | 32.6131 | 12.2789 | 0.3979 | 72.6284        | 12.8364         | 0.7```1     |
 | 0.4652        | 9.95  | 1750 | 0.7291          | 44.4366 | 38.8202 | 43.113  | 43.1423   | 34.1596 | 12.6724 | 0.4049 | 69.7281        | 10.4037         | 0.763      |