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Fill-Mask
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bert
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  The model has been trained for a total of 17 epochs.
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- The loss curve is shown:
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- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6659d7d2f5106a7f0abeaa3d/6Ypq8hLPW3ssOToGcYHDn.png)
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-
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  ## Example Usage
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  ```
@@ -30,4 +27,9 @@ inputs = tokenizer(dna_sequence, return_tensors="pt")
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  # Obtain a DNA embedding, which is a vector of length 768.
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  # The embedding is a representation of this DNA sequence in the model's latent space.
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  embedding = model(**inputs).hidden_states[-1].mean(1).squeeze()
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- ```
 
 
 
 
 
 
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  The model has been trained for a total of 17 epochs.
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  ## Example Usage
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  ```
 
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  # Obtain a DNA embedding, which is a vector of length 768.
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  # The embedding is a representation of this DNA sequence in the model's latent space.
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  embedding = model(**inputs).hidden_states[-1].mean(1).squeeze()
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+ ```
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+
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+ ## Results
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+
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+ The loss curve is shown:
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6659d7d2f5106a7f0abeaa3d/6Ypq8hLPW3ssOToGcYHDn.png)